Number of objectives used in the literature.
\\n\\n
More than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\\n\\nOur breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\\n\\n“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\\n\\nAdditionally, each book published by IntechOpen contains original content and research findings.
\\n\\nWe are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\\n\\n\\n\\n
\\n"}]',published:!0,mainMedia:{caption:"IntechOpen Maintains",originalUrl:"/media/original/113"}},components:[{type:"htmlEditorComponent",content:'
Simba Information has released its Open Access Book Publishing 2020 - 2024 report and has again identified IntechOpen as the world’s largest Open Access book publisher by title count.
\n\nSimba Information is a leading provider for market intelligence and forecasts in the media and publishing industry. The report, published every year, provides an overview and financial outlook for the global professional e-book publishing market.
\n\nIntechOpen, De Gruyter, and Frontiers are the largest OA book publishers by title count, with IntechOpen coming in at first place with 5,101 OA books published, a good 1,782 titles ahead of the nearest competitor.
\n\nSince the first Open Access Book Publishing report published in 2016, IntechOpen has held the top stop each year.
\n\n\n\nMore than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\n\nOur breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\n\n“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\n\nAdditionally, each book published by IntechOpen contains original content and research findings.
\n\nWe are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\n\n\n\n
\n'}],latestNews:[{slug:"intechopen-supports-asapbio-s-new-initiative-publish-your-reviews-20220729",title:"IntechOpen Supports ASAPbio’s New Initiative Publish Your Reviews"},{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"}]},book:{item:{type:"book",id:"9913",leadTitle:null,fullTitle:"Carbon Nanotubes - Redefining the World of Electronics",title:"Carbon Nanotubes",subtitle:"Redefining the World of Electronics",reviewType:"peer-reviewed",abstract:"Carbon Nanotubes - Redefining the World of Electronics is a compendium of current, state-of-the-art information about carbon nanotubes (CNTs) and their potential applications in electronics. Chapters cover such topics as the incorporation of CNTs into electronic devices, CNT-based rubber composites for electronic components, the role of CNTs in different energy storage and conversion systems, and ternary implementations of carbon nanotube field-effect transistor (CNTFET) circuits.",isbn:"978-1-83881-185-3",printIsbn:"978-1-83881-184-6",pdfIsbn:"978-1-83881-186-0",doi:"10.5772/intechopen.87724",price:119,priceEur:129,priceUsd:155,slug:"carbon-nanotubes-redefining-the-world-of-electronics",numberOfPages:182,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"43a22b8570e841b7a26d70159b2f755d",bookSignature:"Prasanta Kumar Ghosh, Kunal Datta and Arti Dinkarrao Rushi",publishedDate:"October 13th 2021",coverURL:"https://cdn.intechopen.com/books/images_new/9913.jpg",numberOfDownloads:2837,numberOfWosCitations:0,numberOfCrossrefCitations:3,numberOfCrossrefCitationsByBook:0,numberOfDimensionsCitations:7,numberOfDimensionsCitationsByBook:0,hasAltmetrics:0,numberOfTotalCitations:10,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"May 28th 2020",dateEndSecondStepPublish:"June 18th 2020",dateEndThirdStepPublish:"August 17th 2020",dateEndFourthStepPublish:"November 5th 2020",dateEndFifthStepPublish:"January 4th 2021",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,7",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"294687",title:"Dr.",name:"Prasanta",middleName:"Kumar",surname:"Ghosh",slug:"prasanta-ghosh",fullName:"Prasanta Ghosh",profilePictureURL:"https://mts.intechopen.com/storage/users/294687/images/system/294687.jpg",biography:"Prasanta Kumar Ghosh is currently an assistant professor in the School of Physics, Dr. Vishwanath Karad MIT World Peace University (MIT-WPU), Pune (MS), India. He is an active researcher in the broad area of organic/inorganic functional materials, including organic field-effect transistors, inorganic/organic hybrids, and advanced sensors based on organic matter and SHI Irradiation. He has fifteen years of experience in the field of nanomaterials, microdevices, and instrumentation. He provides industrial and research solutions with low-cost automation and indigenous instrumentation. He has published fifty-two research papers in various international journals, books, and conferences.",institutionString:"School of Physics, MIT-World Peace University (MIT-WPU)",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"2",totalChapterViews:"0",totalEditedBooks:"1",institution:null}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:{id:"272217",title:"Dr.",name:"Arti",middleName:"Dinkarrao",surname:"Rushi",slug:"arti-rushi",fullName:"Arti Rushi",profilePictureURL:"https://mts.intechopen.com/storage/users/272217/images/system/272217.jpg",biography:"Arti Dinkarrao Rushi is currently an assistant professor in the Department of Electronics and Telecommunication Engineering, Maharashtra Institute of Technology, Aurangabad (MS), India. Her areas of interest include nanotechnology, electrochemical sensors, functionalized materials, macrocyclic compounds, and the application of sensors for environment protection. She has published thirty-nine research papers in various international journals, books, and conferences.",institutionString:"Maharashtra Institute of Technology",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Maharashtra Institute of Technology - Art, Design and Technology University",institutionURL:null,country:{name:"India"}}},coeditorTwo:{id:"294686",title:"Dr.",name:"Kunal",middleName:null,surname:"Datta",slug:"kunal-datta",fullName:"Kunal Datta",profilePictureURL:"https://mts.intechopen.com/storage/users/294686/images/system/294686.jpg",biography:"Kunal Datta is currently an assistant professor in the Industrial Automation Division, Deen Dayal Upadhayay Kaushal Kendra (DDUKK), Dr. Babasaheb Ambedkar Marathwada University, Aurangabad (MS), India. He has fifteen years of research experience in instrumentation, automation, and electrochemical sensors (based on functional nanomaterials, namely single-walled nanotubes, porphyrins, organic conducting polymers, and nanoparticles). His research focuses on the real-time measurement of inorganic/organic air pollutants from the environment, the development of technical didactic tools, and industrial robotics. He has published fifty-four research papers in various international journals, books, and conferences.",institutionString:"Dr. Babasaheb Ambedkar Marathwada University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Dr. Babasaheb Ambedkar Marathwada University",institutionURL:null,country:{name:"India"}}},coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"208",title:"Material Science",slug:"nanotechnology-and-nanomaterials-material-science"}],chapters:[{id:"77983",title:"Introductory Chapter: Introduction to Carbon Nanotubes- Redefining the World of Electronics",doi:"10.5772/intechopen.99112",slug:"introductory-chapter-introduction-to-carbon-nanotubes-redefining-the-world-of-electronics",totalDownloads:117,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:null,signatures:"Kunal Datta, Prasanta Kumar Ghosh and Arti Rushi",downloadPdfUrl:"/chapter/pdf-download/77983",previewPdfUrl:"/chapter/pdf-preview/77983",authors:[{id:"294687",title:"Dr.",name:"Prasanta",surname:"Ghosh",slug:"prasanta-ghosh",fullName:"Prasanta Ghosh"},{id:"426255",title:"Dr.",name:"Kunal",surname:"Datta",slug:"kunal-datta",fullName:"Kunal Datta"},{id:"426256",title:"Dr.",name:"Arti",surname:"D. Rushi",slug:"arti-d.-rushi",fullName:"Arti D. Rushi"}],corrections:null},{id:"75037",title:"Preparation and Characterization of Electrically Conductive Polymer Nanocomposites with Different Carbon Nanoparticles",doi:"10.5772/intechopen.95912",slug:"preparation-and-characterization-of-electrically-conductive-polymer-nanocomposites-with-different-ca",totalDownloads:287,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,abstract:"Carbon nanoparticles possess a combination of high electrical and thermal transport properties, as well as low density and different morphologies that make them a good choice to reinforce plastics. Polymer nanocomposites offer great expectations for new and unexpected applications due to the possibility of changing their electrical/thermal behavior by adding nanoparticles while retaining the flexibility and processability of plastics. The possibility of electrical and thermal conduction in a polymer matrix with low amounts of nanoparticles brings opportunity for high demanding applications such as electrical conductors, heat exchangers, sensors, and actuators. Polyolefin nanocomposites offer a significant challenge due to their insulative nature and low affinity for carbon nanoparticles; due to the latter, new production tendencies are proposed and investigated.",signatures:"Víctor J. Cruz-Delgado, Janett A. Valdez-Garza, José M. Mata-Padilla, Juan G. Martínez-Colunga and Carlos A. Ávila-Orta",downloadPdfUrl:"/chapter/pdf-download/75037",previewPdfUrl:"/chapter/pdf-preview/75037",authors:[{id:"247436",title:"Dr.",name:"Carlos A.",surname:"Ávila-Orta",slug:"carlos-a.-avila-orta",fullName:"Carlos A. Ávila-Orta"},{id:"248817",title:"Dr.",name:"Juan Guillermo",surname:"Martínez-Colunga",slug:"juan-guillermo-martinez-colunga",fullName:"Juan Guillermo Martínez-Colunga"},{id:"248819",title:"BSc.",name:"Janett Anaid",surname:"Valdéz-Garza",slug:"janett-anaid-valdez-garza",fullName:"Janett Anaid Valdéz-Garza"},{id:"263935",title:"Dr.",name:"José Manuel",surname:"Mata-Padilla",slug:"jose-manuel-mata-padilla",fullName:"José Manuel Mata-Padilla"},{id:"324384",title:"Dr.",name:"Victor J.",surname:"Cruz-Delgado",slug:"victor-j.-cruz-delgado",fullName:"Victor J. Cruz-Delgado"}],corrections:null},{id:"77073",title:"Synthesis and Purification of Carbon Nanotubes",doi:"10.5772/intechopen.98221",slug:"synthesis-and-purification-of-carbon-nanotubes",totalDownloads:362,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"In this chapter, we will evaluate the synthesis and purification of carbon nanotubes. Carbon nanotubes are cylindrical molecules that consists of graphene (rolled up of a single-layer carbon atom). A wide variety of synthesis techniques such as arc discharge synthesis, laser ablation of graphite/laser vaporization synthesis method, chemical vapor deposition (CVD), high pressure carbon monoxide synthesis and flame synthesis techniques, have been implemented to grow single and multi-walled carbon nanotubes for technological applications. All of the above methods exploit transition metals, like iron, cobalt, and nickel, as a catalyst. There are number of methods (filtering, chromatography and centrifugation) used to purify the carbon nanotubes, but the degree of purity remained questionable in these methods. In order to enhance the purification extent, alternate techniques such as Gas phase purification, Liquid phase purification and Purification by Intercalation are introduced. Here we will discuss the advantages and disadvantages of these purification routes. It will help researchers in selecting appropriate and effective method for synthesis and purification of carbon nanotubes.",signatures:"Syed Awais Rouf, Zahid Usman, Hafiz Tariq Masood, Abdul Mannan Majeed, Mudassira Sarwar and Waseem Abbas",downloadPdfUrl:"/chapter/pdf-download/77073",previewPdfUrl:"/chapter/pdf-preview/77073",authors:[{id:"322510",title:"Dr.",name:"Syed Awais",surname:"Rouf",slug:"syed-awais-rouf",fullName:"Syed Awais Rouf"},{id:"340877",title:"Mr.",name:"Abdul Mannan",surname:"Majeed",slug:"abdul-mannan-majeed",fullName:"Abdul Mannan Majeed"},{id:"340878",title:"Dr.",name:"Hafiz Tariq",surname:"Masood",slug:"hafiz-tariq-masood",fullName:"Hafiz Tariq Masood"},{id:"340881",title:"Ms.",name:"Mudassira",surname:"Sarwar",slug:"mudassira-sarwar",fullName:"Mudassira Sarwar"},{id:"340883",title:"Mr.",name:"Waseem",surname:"Abbas",slug:"waseem-abbas",fullName:"Waseem Abbas"},{id:"340891",title:"Dr.",name:"Zahid",surname:"Usman",slug:"zahid-usman",fullName:"Zahid Usman"}],corrections:null},{id:"75396",title:"Carbon Nanotubes Reinforced Natural Rubber Composites",doi:"10.5772/intechopen.95913",slug:"carbon-nanotubes-reinforced-natural-rubber-composites",totalDownloads:444,totalCrossrefCites:1,totalDimensionsCites:2,hasAltmetrics:0,abstract:"Several advanced methods have been introduced to disperse CNTs in the NR matrix. Various aspects highlighted in this chapter include the mixing processes such as melt mixing and latex mixing methods. As well as, formations of functional groups on the surfaces of CNT using silane coupling agents (i.e., ex-situ and in-situ functionalization). Moreover, hybrid CNT are beneficial to achieve better electrical conductivity of NR/CNT composites. These efforts are aimed to reduce the percolation threshold concentration in the NR composites for application as conducting composites based on electrically insulating rubber matrix. Sensor application is developed based on conducting NR composites. NR composites showed changing of resistivity during elongation termed as piezoresistivity. The most commonly used rubber matrices such as NR, ENR and IR are mixed with a combination of CNT and CB fillers as hybrid filler. The presence of linkages in the ENR composites results in the least loss of conductivity during external strain. It is found that the conductivity becomes stable after 3000 cycles. This is found to be similar to the NR-CNT/CB composite, while a few cycles are needed for IR-CNT/CB owing to the higher filler agglomeration and poor filler-rubber interactions. This is attributed to the polar chemical interactions between ENR and the functional groups on the surfaces of CNT/CB.",signatures:"Apinya Krainoi, Jobish Johns, Ekwipoo Kalkornsurapranee and Yeampon Nakaramontri",downloadPdfUrl:"/chapter/pdf-download/75396",previewPdfUrl:"/chapter/pdf-preview/75396",authors:[{id:"324372",title:"Dr.",name:"Yeampon",surname:"Nakaramontri",slug:"yeampon-nakaramontri",fullName:"Yeampon Nakaramontri"},{id:"332557",title:"Dr.",name:"Apinya",surname:"Krainoi",slug:"apinya-krainoi",fullName:"Apinya Krainoi"},{id:"332558",title:"Dr.",name:"Jobish",surname:"Johns",slug:"jobish-johns",fullName:"Jobish Johns"},{id:"332559",title:"Dr.",name:"Ekwipoo",surname:"Karnkornsurapranee",slug:"ekwipoo-karnkornsurapranee",fullName:"Ekwipoo Karnkornsurapranee"},{id:"332560",title:"Dr.",name:"Yeampon",surname:"Nakaramontri",slug:"yeampon-nakaramontri",fullName:"Yeampon Nakaramontri"}],corrections:null},{id:"73704",title:"Carbon Nanotubes as Reinforcing Nanomaterials for Rubbers Used in Electronics",doi:"10.5772/intechopen.94061",slug:"carbon-nanotubes-as-reinforcing-nanomaterials-for-rubbers-used-in-electronics",totalDownloads:414,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:0,abstract:"The field of electronics involves complex systems where the active and passive electronic devices are integrated on the rubber substrate, e.g., silicone (Q), which provides, through potting, a strong assembly of these devices on the circuit board. Several other rubbers are employed in the field to strengthen, insulate and seal the components of the electronic machines and instruments, and therefore protect them against damage. These rubbers are typically strengthened and toughened using carbon black (CB). However, due to its noticeable drawbacks, recent research in the field of rubber and electronics has suggested the use of carbon nanotubes (CNTs) as alternative reinforcing fillers to produce electronics rubber composites that do not only have enhanced electrical conductiv¬ity, thermal stability, electromagnetic interference (EMI) shielding, weatherability and insulation properties, but also offer outstanding stretchability, bendability and tear strength under frequent elastic deformation. These performances are similar for both single-walled carbon nanotubes (SWCNTs) and multi-walled carbon nanotubes (MWCNTs) in both the functional and structural composites. Although SWCNTs can result in relatively better homogeneity than MWCNTs, most rubbers often constitute MWCNTs because they are relatively cheaper. The great potential of rubber-CNTs composites being extensively used in the field of electronics is explored in this chapter.",signatures:"Jabulani I. Gumede, James Carson and Shanganyane P. Hlangothi",downloadPdfUrl:"/chapter/pdf-download/73704",previewPdfUrl:"/chapter/pdf-preview/73704",authors:[{id:"323225",title:"Mr.",name:"Jabulani I.",surname:"Gumede",slug:"jabulani-i.-gumede",fullName:"Jabulani I. Gumede"},{id:"327670",title:"Dr.",name:"James",surname:"Carson",slug:"james-carson",fullName:"James Carson"},{id:"327671",title:"Dr.",name:"Shanganyane P.",surname:"Hlangothi",slug:"shanganyane-p.-hlangothi",fullName:"Shanganyane P. Hlangothi"}],corrections:null},{id:"73737",title:"Carbon Nanotubes: Applications to Energy Storage Devices",doi:"10.5772/intechopen.94155",slug:"carbon-nanotubes-applications-to-energy-storage-devices",totalDownloads:746,totalCrossrefCites:1,totalDimensionsCites:3,hasAltmetrics:0,abstract:"Carbon nanotubes (CNTs) are an extraordinary discovery in the area of science and technology. Engineering them properly holds the promise of opening new avenues for future development of many other materials for diverse applications. Carbon nanotubes have open structure and enriched chirality, which enable improvements the properties and performances of other materials when CNTs are incorporated in them. Energy storage systems have been using carbon nanotubes either as an additive to improve electronic conductivity of cathode materials or as an active anode component depending upon structural and morphological specifications. Furthermore, they have also been used directly as the electrode material in supercapacitors and fuel cells. Therefore, CNTs demand a huge importance due to their underlying properties and prospective applications in the energy storage research fields. There are different kinds of carbon nanotubes which have been successfully used in batteries, supercapacitors, fuel cells and other energy storage systems. This chapter focuses on the role of CNTs in the different energy storage and conversion systems and impact of their structure and morphology on the electrochemical performances and storage mechanisms.",signatures:"Ruhul Amin, Petla Ramesh Kumar and Ilias Belharouak",downloadPdfUrl:"/chapter/pdf-download/73737",previewPdfUrl:"/chapter/pdf-preview/73737",authors:[{id:"324187",title:"Dr.",name:"Ruhul",surname:"Amin",slug:"ruhul-amin",fullName:"Ruhul Amin"},{id:"329299",title:"Dr.",name:"P. Ramesh",surname:"Kumar",slug:"p.-ramesh-kumar",fullName:"P. Ramesh Kumar"}],corrections:null},{id:"76853",title:"Applications of Carbon Based Materials in Developing Advanced Energy Storage Devices",doi:"10.5772/intechopen.97651",slug:"applications-of-carbon-based-materials-in-developing-advanced-energy-storage-devices",totalDownloads:149,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"With the increasing pressure of population, the energy demand is growing explosively. By 2050, it is expected that the world population may reach to about 9 billion which may result in the increase of energy requirement to about 12.5 trillion watts. Due to increasing pressures of population, industries and technology, concerns to find possibilities to cope with increasing demand of energy resources, arise. Although the renewable energy resources including fossil fuels, wind, water and solar energy have been used for a long time to fulfill the energy requirements, but they need efficient conversions and storage techniques and are responsible for causing environmental pollution due to greenhouse gases as well. It is thus noteworthy to develop methods for the generation and storage of renewable energy devices that can replace the conventional energy resources to meet the requirement of energy consumption. Due to high energy demands, the sustainable energy storage devices have remained the subject of interest for scientists in the history, however, the traditional methods are not efficient enough to fulfill the energy requirements. In the present era, among other variety of advanced treatments, nano-sciences have attracted the attention of the scientists. While talking about nano-science, one cannot move on without admiring the extraordinary features of carbon nanotubes (CNTs) and other carbon based materials. CNTs are on the cutting edge of nano science research and finding enormous applications in energy storage devices. Excellent adsorption capabilities, high surface area, better electrical conductivity, high mechanical strength, corrosion resistance, high aspect ratio and good chemical and physical properties of CNTs have grabbed tremendous attention worldwide. Their charge transfer properties make them favorable for energy conversion applications. The limitation to the laboratory research on CNTs for energy storage techniques due to low specific capacitance and limited electrochemical performance can be overcome by surface functionalization using surface functional groups that can enhance their electrical and dispersion properties. In this chapter, ways CNTs employed to boost the abilities of the existing material used to store and transfer of energy have been discussed critically. Moreover, how anisotropic properties of CNTs play important role in increasing the energy storage capabilities of functional materials. It will also be discussed how various kinds of materials can be combined along CNTs to get better results.",signatures:"Maria Tariq, Tajamal Hussain, Adnan Mujahid, Mirza Nadeem Ahmad, Muhammad Imran Din, Azeem Intisar and Muhammad Zahid",downloadPdfUrl:"/chapter/pdf-download/76853",previewPdfUrl:"/chapter/pdf-preview/76853",authors:[{id:"191381",title:"Dr.",name:"Tajamal",surname:"Hussain",slug:"tajamal-hussain",fullName:"Tajamal Hussain"},{id:"287654",title:"Dr.",name:"Muhammad",surname:"Zahid",slug:"muhammad-zahid",fullName:"Muhammad Zahid"},{id:"336260",title:"Ms.",name:"Maria",surname:"Tariq",slug:"maria-tariq",fullName:"Maria Tariq"},{id:"336261",title:"Dr.",name:"Adnan",surname:"Mujahid",slug:"adnan-mujahid",fullName:"Adnan Mujahid"},{id:"336262",title:"Dr.",name:"Mirza Nadeem",surname:"Ahmad",slug:"mirza-nadeem-ahmad",fullName:"Mirza Nadeem Ahmad"},{id:"336263",title:"Dr.",name:"Muhammad Imran",surname:"Din",slug:"muhammad-imran-din",fullName:"Muhammad Imran Din"},{id:"336265",title:"Dr.",name:"Azeem",surname:"Intisar",slug:"azeem-intisar",fullName:"Azeem Intisar"}],corrections:null},{id:"74683",title:"Fault Tolerance in Carbon Nanotube Transistors Based Multi Valued Logic",doi:"10.5772/intechopen.95361",slug:"fault-tolerance-in-carbon-nanotube-transistors-based-multi-valued-logic",totalDownloads:318,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"This Chapter presents a solution for fault-tolerance in Multi-Valued Logic (MVL) circuits comprised of Carbon Nano-Tube Field Effect Transistors (CNTFET). This chapter reviews basic primitives of MVL and describes ternary implementations of CNTFET circuits. Finally, this chapter describes a method for error correction called Restorative Feedback (RFB). The RFB method is a variant of Triple-Modular Redundancy (TMR) that utilizes the fault masking capabilities of the Muller C element to provide added protection against noisy transient faults. Fault tolerant properties of Muller C element is discussed and error correction capability of RFB method is demonstrated in detail.",signatures:"Gopalakrishnan Sundararajan",downloadPdfUrl:"/chapter/pdf-download/74683",previewPdfUrl:"/chapter/pdf-preview/74683",authors:[{id:"325537",title:"Dr.",name:"Gopal",surname:"Sundar",slug:"gopal-sundar",fullName:"Gopal Sundar"}],corrections:null}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},subseries:null,tags:null},relatedBooks:[{type:"book",id:"7640",title:"Perspective of Carbon Nanotubes",subtitle:null,isOpenForSubmission:!1,hash:"8b85a9957fad5206369eadf0c1ffa27d",slug:"perspective-of-carbon-nanotubes",bookSignature:"Hosam El-Din Saleh and Said Moawad Mohamed El-Sheikh",coverURL:"https://cdn.intechopen.com/books/images_new/7640.jpg",editedByType:"Edited by",editors:[{id:"144691",title:"Prof.",name:"Hosam M.",surname:"Saleh",slug:"hosam-m.-saleh",fullName:"Hosam M. 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There is only a small percentage of the world’s population that live outside their countries of birth or origin, but migration is still an important phenomenon on the political agenda of some countries. The movement of people across borders is a potential problem for almost all countries as it is nearly impossible to completely control immigration flows. The management of deportation is a mandatory function of the Department of Home Affairs (DHA) in the Republic of South Africa in terms of Section 34 of the Immigration Act 13 of 2002 as amended [1]. The DHA has two core businesses which are civic services and Immigration Services (IMS). Deportation management falls under the branch of IMS. IMS has further three business units namely, Port Control, Permitting (Visas), Asylum Seekers Management and Inspectorate. Inspectorate is established in terms of Section 33 of the Immigration Act 13 of 2002 as amended. The management of deportation is one of the functions of the Inspectorate, which is the law enforcement arm of the department [2]. The responsibility of the inspectorate is to comply with the Immigration Act. It is the responsibility of the deportation directorate to deport Illegal Foreigners (IFs) who are detected and arrested for contravening the Immigration Act.
An immigrant is someone who voluntarily chooses to leave his or her own country and make a new life in another country. Movement is the established pattern of migration and is both a strategy of survival and livelihood and inseparable from identity. The daily mobility rate has declined with increasing age and duration of residence. Forced migration is defined as the coerced movement of a person or people away from their home or home region to another country [3].
The literature has shown that elderly people who live with adult children leave the country due to poverty or their disabilities [4]. Moreover, some scholars have suggested that many of the extended households mainly benefit the child in migration [5]. In addition, migration internally shows movement within the country and this is called internal displacement.
The recent policies such as liberalisation, macro-economic reforms, decentralisation, and regionalisation, and food security, for example, are likely to influence population movements. The government must plan for migrations because there is a correlation between development and population movement. Policy documents do not provide sufficient reference to migration and the controlling and limiting of migration remains a state objective [6].
In current development planning, the development-migration relationship plays out in two main ways. First, development strategies are proposed to reduce population movements that are harmful to development. Second, population movements are consequences, often unintended, of development interventions. For example, structural adjustment measures indirectly induce displacement. It has also been noted that sometimes forced population displacement is justified to further development and provide an opportunity for national poverty reduction measures. It was found that infrastructural development projects directly bring about population displacement and resettlement or for the alleviation of overcrowding and land-tenure reform in South Africa [7].
The most notable characteristic of deportation statistics in South Africa is their consistency in rankings and growth patterns. Mozambicans continue to pose the greatest challenge as they comprised 87% of all deportations in South Africa in 1996. However, Zimbabweans remain the second major problem as they have steadily increased as a percentage of the total from 8% in 1996 to 43% by 2004 [8].
The exponential increase in deportations from 1994 to 1996, reflects the restrictions represented in the 1995 amendments to the Aliens Control Act, 96 of 1991 [9]. The end of the Apartheid regime with the beginning of democracy in South Africa and the promise of higher employment rates, had an impact on illegal migration as it clearly increased the number. The amendments show the government’s harsh perceptions of illegal migrants in South Africa [10]. Moreover, statistics on the immigrants who were detained at the Lindela Repatriation Centre indicate that the average age of detainees is 25.8 years. Moreover, the proportions of males to females are equal [11].
Various governments consider numerous methods to decrease access by foreigners. Sometimes this is an inevitable result that immigrants continue to cross barriers and live within the country without proper documentation. This constitutes illegal immigration [12]. There was mass migration in the onset of nineteenth- and twentieth-century patterns of mass migration that were much lower compared to the present. This was caused by the increasing income inequality and the widening gap between rich and poor countries that only intensifies the pressure on those who can find employment in other countries. An important theme that comes strongly across in global migration and the world economy is the potential gain in terms of global income if migration controls and restrictions were to be released [13].
The data from the international migration network show that overall, there has been a reduction in migration. However, whilst migration flows are high in absolute terms, in relative terms they are not. The long view of migration compares mass migrations before the First World War and the Second World War. At both stages, globalisation promoted the movement of people but also increased the development gap between sending and receiving countries. The main difference between the two periods of world history lies in the fact that it was more favourable in the first period compared to the restrictions on immigration characteristic of the recent period. Presently, there is a massive return of migrants to their countries of origin. In previous depressions there was always somewhere else to go, but not this time [14].
It has been estimated that between 2.5 million and 5 million or up to 7 million irregular migrants are present in South Africa as reported by the Department of Home Affairs [15]. There are many types of migration occurring in the country. The different types of migration can be characterised as highly skilled migration, qualified and educated professionals, and unskilled and illegal migration. Unskilled and illegal migrants enter the country after the political transitions from the Apartheid regime to democratic South Africa in 1994 [16]. These foreign migrants experience harassment by police officials. Police officers abuse their power by requesting bribes or by abusing the migrants when checking migrants for their identity document (ID) which is against their human rights [17].
Moreover, migrants are at the risk of being unnecessarily arrested and detained for longer periods which violates the law [18]. Usually, illegal migration is less beneficial for immigrants as they do not have access to a full range of employment. They must accept lower wages for the same job and pay for higher immigration costs.
The movement of migrants fluctuates because of factors that include geographic proximity, the precedent, sociocultural issues, communications and technology, and demographic, environmental, economic, and political considerations.
South Africa has seen increased pressure on resources such as housing, strains of overpopulation and resultant transmissions of disease leading to increased expenditure and social and political tensions. Migrants, therefore, are marginalised and have a low-status in society with low-paid employment [19].
Many people enter South Africa illegally. One way of controlling this movement is by deportation. Deportation is the expulsion of a person or group of people from a place or country. Therefore, South African and international literature will be used to identify factors that lead to ineffective management and factors that influence illegal immigrants to enter a country. Thus, saving South Africa millions of rands in revenue [20].
The literature suggests that there are three theories of migration, in which the purposes of migration are not the same and do not supersede another. The first one is macro theories which emphasise the structural, objective conditions that act as “push” and “pull” factors for migration. The push factors are the things about a country that make it not desirable and make people want to leave for reasons such as political and economic factors which leads to unemployment conditions, poor wages, or poor per capita income and political persecution compared to the host country. The pull factors are the characteristics of the host country that make it desirable and people want to be in that country for those benefits. These pull factors may include labour and migration legislation situations, better amenities, living conditions, education, health care, and many others [21].
In addition, forced migration may be caused by factors such as state repression or fear of persecution or civil war. All these theorists agree that macro conditions such as those are vital because they cause forced migration and pioneer voluntary migration. Pioneer migrants are the first individuals or groups of migrants from a given country or area moving to another country or area. These migrations are not voluntary but rather forced upon the individuals [3].
Although migrants are persistent in their quests to enter South Africa they are ill-equipped in dealing with the economic conditions and legislation in receiving countries. Rates of flow differ from mass emigration to almost no mobility [3]. These rates are influenced by political instability and the pursuit of economic opportunities.
The systems and networks are particularly important for meso-theory analysis regarding the population size. Groups of countries can be linked economically, politically, and culturally which further influences migration flows. These networks refer to the individual and collective factors with symbiotic ties that link them together [22].
Besides, once formed, social networks can substantially influence the direction and volume of migration flows, providing resources that help people to move, such as information, contacts, economic, and social support.
The micro-theories are factors that attract or give reasons for individuals to migrate, weighing the cost-benefits of migrating. This may include the financial resources invested in migrating and integration in the country of destination, while benefits could include a higher wage. The micro-perspective provides a critical analysis in terms of pointing out how people internally process and assess the options for migration. There are forms of check or control for macro- and meso-theories, in relating to how individuals make decisions on the fact of objectivity [23].
This was a policy document and literature review study. South African Immigration Act, legal framework documents were reviewed. The literature review was conducted between October and November 2020 using Google Scholar and Ebscohost search engine. The following keywords were used to search the literature: Immigration, Migration, Deportation, and illegal foreigners. Initially, a total of 250 abstracts were retrieved for relevance. After careful consideration, 53 articles were found suitable for the study. Based on the policy and legal documents, together with literature, we summarised the management of illegal deportation of undocumented migrants as well as, the challenges faced by the DHA of South Africa.
The Immigration Act manages how foreigners enter, depart from, and reside in South Africa. People who do not follow the Immigration Act can be arrested, detained at the Lindela Holding Facility, and then deported. The detention and deportation procedure are conditional to many legal protections that shield the constitutional rights of foreigners who are in detention or who are going to be deported [24].
The Immigration Act defines an ‘illegal foreigner’ as a person who enters South Africa in breach of the Immigration Act, or someone who does not have the correct documentation such as an asylum seeker permit, legal recognition of refugee status, or a valid permit or visa in their passport. The term ‘illegal foreigner’ is an issue as it creates the perception that the person is a criminal. A person cannot be ‘illegal’ just because they do not have the correct documents in terms of a country’s immigration laws [25].
An illegal foreigner may involuntarily have to leave South Africa via a deportation process administered by the Department of Home Affairs under detention legislation outlined in the Immigration Act. Generally, this person would be returned to their country of origin. The Lindela Holding Facility would detain the migrant until this occurs, as set out by Sections 32 and 34 of the Immigration Act.
The Department of Home Affairs works with officials from the foreigner’s country of origin to guarantee they will be received once they return as part of the process of deportation. Deportation is the function of the state and should be done by following the law [26].
During the Apartheid regime, South Africa had a set of legislation to control the movement of the non-White population that was linked to employment opportunities that only allowed low to semi-skilled work known as the pass laws. The Act only permitted the White population into urban areas while all non-White adult men had to always carry passes to justify their presence in those areas. Anyone found without the correct documentation were to be arrested and sent to rural areas. This law was created to restrict the control of movements of the non-White population within the country. This included constant coercion and the presence of a submissive workforce only when and where it was needed [27].
Moreover, from 1960, this system of controlling the movements of the non-White population was extended to the foreign migrants known as the ‘two gates’ policy. The Aliens Control Act almost did not allow any non-White migrant workers to enter the country. There were also a set of mutual agreements with countries across the border of South Africa. These agreements allowed foreign migrants into the country as they were needed by economic sectors such as mining or commercial farming [28].
The Aliens Control Act has evolved since 1937 with updates occurring in the 1960s and 1970s. The original focus involved restricting Jewish immigration to South Africa by enforcing police controls at various entry points and arresting those migrants who did not have the relevant documentation [29]. During this period, this Act was only available to White inhabitants employing migrants. Since South Africa’s democratic government came into power in 1994, a new Immigration Act was adopted in 2002 that replaced the Refugees Act of 1998 [30]. However, scholars have reported that public officials, such as migration and police officers, may retain historical attitudes on South African migration policies [31].
After the demise of the Apartheid era, new regulations replaced the previous legal framework concerning migration. At present, these regulations are outlined in the 2002 Immigration Act, the 1998 Refugees Act and the Constitution of 1996. The former, which was amended in 2004, defines the enforcement and monitoring principles as well as the general objectives of the migration policies regarding temporary and permanent residence.
It is reported that during Apartheid the Alien Control Act opened a path for foreigners to become South African residents. The Act did not solely focus on opposing illegal migration and it particularly outlined the protection of migrants’ rights [32].
There were numerous ways to receive temporary residence in South Africa. For example, employment, education, visiting or meeting family, applying for asylum, and cross-border travels as outlined in the Immigration Act of 2002 [33]. The Act also establishes special work permits, which are easier to obtain for people with exceptional skills or qualifications as it benefits South Africa to increase their professional and skilled workers. Moreover, the Immigration Act also maintains the category of ‘corporate work permit’.
Corporate companies may employ migrants by applying directly to the Department of Home Affairs while placing financial guarantees. However, due respect regarding the migration regulations needs to be granted by the provision of numbers employed and their job descriptions [34]. In some cases, such as in the mining and agricultural sectors, the Act enables the government to waiver, reduce, or even end certain requirements with foreign countries regarding permits for work migrants.
The Immigration Act provides a robust mechanism to maintain a balance between the needs of the South African economy and the high level of unemployment in the country [35].
According to the Immigration Act (2002), an illegal or legal immigrant will temporarily or permanently settle in the Republic of South Africa. Regularisation of an illegal immigrant in South Africa occurs as soon as he/she receives the proper documentation, which is in accordance with the Immigration Act. Following the successful completion of this process, the applicant’s immigration status changes to permanent residence.
Any foreign national or immigrant who is not properly documented according to the Immigration Act is liable to an offence of contravening the Immigration Act and will be either forcefully or voluntarily deported. This is to ensure the efficiency of planning and budgeting by the state. To create a history of sustainability for humans, good national governance is an important component [36].
An issue of immigration is to ascertain the extent of illegal immigration and its main features, which is fundamental for efficient management of the phenomenon. However, the official figures are inadequate, leading many experts to estimate the data through direct measures [37].
Illegal immigrants face numerous hindrances by being compelled to work in the informal economy as comparatively having a legal status opens up a wide variety of employment opportunities with resulting higher wages and lower immigration costs. Illegal immigrants feel that they need to pay for false documents to avoid employment in poor working conditions.
Moreover, on average, their wages are lower than those paid to legal immigrants.
Even though illegal immigrants have different status results and characteristics from legal immigrants, their motivations to migrate are the same; they look for ways to improve their economic and social situations.
Other studies have debated issues such as national security and civil rights but in this chapter, the emphasis is on the economic consequences of illegal immigrants and their effect on goods and services, social benefits and welfare, and income distribution [38].
Employers benefit from illegal labour that is abundant, inexpensive and flexible, with illegal immigration responding faster to economic incentives compared to legal immigration. Ebbs and flows in the markets of the expanding and contracting economic periods in both the host and the sending economies are more visible in illegal immigration [39].
The process for acquiring documentation poses logistical and financial issues, and what is required for people is not necessarily clear. For some people, the fee of R430 for a visa application may be high and may discourage migrants from applying for this at all which makes illegal entry into the country more appealing [40].
Furthermore, there may be cross-border ethnic similarities and the absence of solid barriers, which may lead to an extension of internal migration that is still considered to be irregular immigration. People who live along borders may cross these borders often without the proper documentation to carry out their daily business of trading, visiting family, attending school, or doing shopping. A potential solution is to create a cross-border system that facilitates movement within a prescribed area across a border. The Immigration Act makes an exception regarding a cross-border permit for South Africa’s immediate neighbours. However, the regulations neither provide a clear indication on how to make an application, nor do they contain an example of the permit itself [41].
In addition, it may be difficult or impossible for some migrants to meet the requirements to attain a permit. For example, many of the migrants who want to enter South Africa in search of employment may not qualify for a work permit. This may lead to documents being forged or tampered with. Fraudulent entry has been accomplished either by going undetected or with the complicity of corrupt officials in South Africa.
The record of arrests of department officials on charges of corruption generally indicates where the corrupting influence comes from and has significantly implicated Chinese, Pakistani, and Nigerian migrants. The intention of securing services or rights to which they are not entitled within South Africa encourages fraud. A specific issue is that where the department must handle is fraudulent citizenship obtained through the delayed registration of births [42].
Moreover, the issue is the registering of fraudulent marriages between foreigners and South Africans. In both these situations, corruption within the department makes it possible for irregular migrants to establish their presence through fraudulent means. Moreover, a lack of resources and inefficiency of the department, causing delayed, incorrect or invalid delivery of citizenship or residential services result in migrants not having the proper documentation which may lead to their irregular or illegal migrant status [43].
Deportation is the action or procedure aimed at illegal foreigners to leave the country in terms of the Immigration Act (Immigration Act, 2002). Some authors define deportation as the removal of an alien out of the country. This is simply because his or her presence is deemed inappropriate with the public welfare. Also, this happens without any punishment being imposed or contemplated under the laws of the country. In the USA, most of the people who are deported are normally those who have also committed crimes within the country [44].
The data from the Department of Home Affairs have shown that there is a pattern of illegal migrants who re-enter South Africa after being deported once within six months [45]. Most of these returnees are from the SADC countries who simply jump the borders such as Zimbabweans. This phenomenon has been termed the ‘revolving door syndrome’. The porous borders greatly contribute to this phenomenon. In November 2003 media briefing, the Director-General began to draw attention to this concept as it was an increasing challenge for the country. The revolving door syndrome is a difficult concept to measure. The recent introduction of the fingerprinting system should be an attempt to address this problem [46].
Furthermore, this phenomenon implies that the deportation process does not have much preventative effect. If irregular migrants are not stopped by their experience of deportation, the process becomes redundant. It has also been noted that some illegal immigrants present themselves to immigration officers for arrest and deportation around the Christmas season as a way of receiving a free ride home. This has led the department to pause deportations over this period [47].
The effectiveness of the deportation process is questioned by the human rights community, as while touring the Lindela Holding Facility, the South African Human Rights Commissioner opined that the system of detention and resulting deportation was unsuccessful and this was concurred by the Lawyers for Human Rights. The detention and repatriation process was believed to promote illegal migration into South Africa according to the Deputy Chairperson of the Commission. This process has been termed as the ‘revolving door syndrome’ [48].
Pull and push factors influence the success of the migrants to return to their countries of origin. For instance, having a family in the receiving country would motivate them to return to South Africa. Also, should there be a lack of support, financial and otherwise, from family members, migrants would be motivated to return to the receiving country again, in this case, South Africa. Similarly, if the repatriated family member had committed a major criminal offence, the relatives would be loath to support them [49].
The Linda Holding Facility is the largest detention centre for undocumented migrants in South Africa. Literature shows that the current management of deportation is unfair and ineffective [50]. There are various issues experienced by detainees during their arrests such as the arrest and detention of foreigners with valid documents, failure to take various steps to verify immigration status, failure to inform suspected illegal foreigners of the reason for their arrest, physical harm during the arrest process, lack of access to cell phones and refusal to allow detained suspects to call relatives or friends, systemic problems with the DHA’s record-keeping and lack of communication between the DHA and the police, and lastly detention of suspected illegal foreigners for more than two days which is a violation of their human rights law as well as the immigration law. These issues illustrate that problems in the detention and deportation process are not limited to the actions of the DHA alone [26].
The best alternative to resolving some of the issues mentioned above is through coordination and cooperation with other departments, particularly, the South African Police Services. Moreover, one of the main issues identified was the lack of effective verification of an individual’s immigration status before being sent to Lindela Holding Facility. This is due to various reasons, including corruption and abuse of power, insufficient resources, and the failure to follow legal procedures by providing individuals with an opportunity to confirm their status with supporting documents when it is reasonable and practicable. Due to these issues, individuals with illegal immigration status frequently find themselves at the Lindela Holding Facility. This increases the burden on the DHA, in terms of verification, transport, and administration [51].
The inefficiency and abuse that is evident in the Lindela Holding Facility reflect poorly on the vision of a democratic South Africa as it jeopardises the rule of law and is directly in conflict with the country’s respect for human rights, regardless of an immigrant’s legal status. This aspect is a vital contribution to a functioning democracy [52].
The Lawyers for Human Rights (LHR) frequently visit this facility and have represented many of the individuals illegally detained there. It is in the interest of the government to remedy the causes of these legal violations as most of them have resulted in costs and punitive damages against the DHA. The overall cost of detaining migrants has raised the costs of detention [53].
Detainees at the Lindela Centre have expressed feelings of frustration and legal uncertainty [54]. Despite the numerous South African laws that protect illegal immigrants, abuses of power are still evident. Detainees have prolonged, indefinite periods of detention with a lack of information on their legal status. Some individuals were aware of the appeal process through reviews which would enable them to challenge their circumstances. However, others reported being unable to access these rights due to the barriers in the facility. Immigration officials within the DHA holding facility were unavailable to detainees who reported only having contact with Bosasa staff who were responsible for the daily operations there. Corruption was a common theme that prevented them from exercising their rights of review and appeal [53].
Asylum seekers in Lindela who are at risk of prosecution could be sent back to their countries of origin by the DHA which is a direct violation of the international prohibition against non-refoulement [55]. Those asylum seekers who were released from the facility and told to report to the refugee reception office were rearrested which indicates a lack of communication between officials in Lindela and the reception offices [56].
There are implications from the literature on the migration patterns in South Africa. First and foremost, the Department of Home Affairs must address its ineffective administrative processes and fulfil its mandate cost-effectively and legally that upholds the rights of all individuals. A total of 29% of the respondents were not advised on the reasons for their arrest, and 10% reported being injured during the arrest. Those arrested by the SAPS were more than twice as likely to have suffered an injury during the arrest which indicates that these police personnel frequently abuse their power by causing physical harm to the migrants which is a violation of their human rights. Individuals arrested by immigration officials could make calls more often (57%) than those arrested by the SAPS (41%) [57].
Furthermore, it has been reported that there were problems with the verification process when the individuals were arrested on suspicion of being illegal foreigners. The statistics reported that 53% of the respondents had asylum permits and only 21% of the respondents were undocumented [58].
In some cases, the individuals detained as illegal foreigners did hold valid refugee IDs, asylum seeker permits, or even South African IDs [59]. This highlights the deficiencies in the verification process as it is evident that these individuals have not had their legal status verified. This study illustrates that the management of deportations within Lindela is shown to be ineffective.
Requests for funds were reported by 21% of the detainees to avoid being physically harmed, further detained, or arrested. These requests arose from interactions with DHA officials (35%), Bosasa employees (8%), and police officers (50%). At the facility itself, requests for money was mentioned to secure their release and avoid deportation waiting periods [60].
The DHA officials should understand immigration laws while performing official work. The tracing of people in the Republic of South Africa is important but illegal immigrants are not easy to detect because they do not have a permanent place of residence for illegal immigrants in South Africa. The arrest of illegal immigrants must be done according to the law and the constitution. Several pull factors lead to re-entry into South Africa after deportation and these include property in the republic, and family and social networks, among others. These pull factors must be addressed during the deportation process so that they are not tempted to get back to the republic. The DHA official must understand these pull factors whilst executing the deportation processes.
There are several challenges to illegal immigration in South Africa, but the most important ones include poor border control systems. South Africa has more than 100 gazetted entry points and the controls are poor. Moreover, IT systems are not integrated and resources are limited.
This study has provided insights into the management of deportation of an undocumented illegal immigrant in South Africa which was lacking in the literature. In addition, policymakers may use the findings of this study to design robust policies to secure the border and protect citizens from the negative consequence of illegal migration such as drugs, fraud and others which is on the rise in the Republic of South Africa.
The main objective of the construction industry is to directly and indirectly provide people’s daily needs. Mostly, a construction project involves the use of different resources (e.g., machinery, materials, manpower, etc.) to produce the final product (e.g., a building, a bridge, a water distribution system, etc.) that serves the targeted users’ needs. The difficulties that are met in construction projects include budget limitations, contractual time constraints, safety and health issues, sustainability ratings, local building codes, the desired level of quality, to name but a few. Consequently, a construction project has multiple objectives including maximum productivity, minimum cost, minimum duration, specified quality, safety, and sustainability. Making decisions is difficult when one wants to reach the optimal solution for a combination of objectives.
\nConstruction practitioners have been using single-objective optimization strategies to meet the desired level of construction objectives. However, because the multiple objectives of construction projects often conflict with each other, single-objective optimization does not offer practical solutions, as optimizing one objective would often adversely affect the other objectives that are not being optimized. As a result, some projects fail to meet some of the objectives. In order to avoid such failures, researchers have developed tools that can help efficiently manage construction projects and achieve the required objectives. These tools include many multi-objective optimization approaches, each of which has its own advantages and drawbacks when used in some scenarios with different sets of objectives.
\nA review is presented in this chapter of the various multi-objective optimization approaches used in recent studies in the construction industry to highlight the strengths and weaknesses of these approaches when used in different scenarios.
\nA total of 55 studies that applied multi-objective optimization methods in the construction industry are reviewed in this chapter. To avoid overlapping and redundancy of reviews with Evins’ work [1], the review in this chapter includes only the recent studies which were published in the period late 2012 to early 2016. Evins [1] covered the period of 1990 to late 2012 and conducted a review of the studies that applied optimization methods in sustainable building design.
\nThe 55 studies are reviewed relative to (1) the optimization method, (2) the project phase, (3) the optimization problem, (4) the type and number of targeted objectives, (5) the example used to test a model, and (6) the comparison with other methods when applicable.
\nThe number of optimization methods found in the review of the 55 papers was 16. These 16 methods and their usage frequency are presented in Figure 1, which shows that NSGA-II is the most used method (14 times) followed by a hybrid method (12 times) which pairs two or more methods for the optimization process. The acronyms in this figure are spelled out in Table 1.
\nFrequency of methods used in literature.
Optimization method | \nNumber of objectives | \n|||||
---|---|---|---|---|---|---|
2 | \n3 | \n4 | \n5 | \n6 | \n7 | \n|
Genetic algorithms (GA) | \n2 | \n3 | \n— | \n— | \n— | \n— | \n
Differential evolution (DE) | \n1 | \n3 | \n— | \n— | \n— | \n— | \n
Strength Pareto evolutionary algorithm (SPEA) | \n— | \n1 | \n— | \n— | \n— | \n— | \n
Non-dominated sorting genetic algorithm-II (NSGA-II) | \n8 | \n6 | \n— | \n— | \n— | \n— | \n
Niched Pareto genetic algorithm (NPGA) | \n— | \n1 | \n— | \n— | \n— | \n— | \n
Multi-objective genetic algorithm (MOGA) | \n1 | \n— | \n— | \n— | \n1 | \n1 | \n
Particle swarm optimization (PSO) | \n3 | \n3 | \n— | \n2 | \n— | \n— | \n
Ant colony optimization (ACO) | \n1 | \n— | \n— | \n— | \n— | \n— | \n
Analytic network process (ANP) | \n— | \n— | \n1 | \n— | \n— | \n— | \n
Shuffled frog-leaping algorithm (SFLA) | \n— | \n1 | \n— | \n— | \n— | \n— | \n
Simulated annealing algorithm (SA) | \n1 | \n— | \n— | \n— | \n— | \n— | \n
Plant growth simulation algorithm (PGSA) | \n1 | \n— | \n— | \n— | \n— | \n— | \n
Hungarian algorithm (HA) | \n1 | \n— | \n— | \n— | \n— | \n— | \n
Mixed-integer nonlinear programming (MINLP) | \n2 | \n— | \n— | \n— | \n— | \n— | \n
Hybrid methods | \n6 | \n6 | \n— | \n— | \n— | \n— | \n
Total (56 methods) | \n27 | \n24 | \n1 | \n2 | \n1 | \n1 | \n
Number of objectives used in the literature.
These optimization methods were used to tackle different numbers of objectives at a time. The number of objectives that was simultaneously optimized ranged between 2 and 7. The most common number of objectives in a study was 2 or 3 objectives (27 and 24 times, respectively) distributed by methods as shown in Table 1. The least common number of objectives considered in a study was 4, 6, and 7 (one time each). It should be noted that one of the 55 papers used two optimization methods, i.e., NSGA-II and PSO. Therefore, the total number of methods used in the 55 papers is 56.
\nAs expected, the large majority of the studies optimized two or three objectives that concern most practitioners. The number of times the objectives were used is presented in Table 2. Among the objectives used in the 55 papers, cost was the mostly optimized, accounting for 93% (51 times) of the total number of studies, duration was the second most optimized objective accounting for 42% (23 times), and the energy and environment category was the third most optimized with 31% (17 times). The rating system score was used only 3 times, i.e., in only 5% of the studies, which represents the least optimized objective.
\nObjective | \nNumber of times objective used in studies | \n
---|---|
Cost | \n51 | \n
Duration | \n23 | \n
Quality | \n7 | \n
Resources | \n7 | \n
Energy and environment | \n17 | \n
Thermal | \n13 | \n
Safety | \n6 | \n
Rating system score | \n3 | \n
Other | \n23 | \n
Number of times the objectives were used in the 55 studies.
GA is one of the popular evolutionary algorithms used by researchers. GA uses the concept of chromosomes to present the possible solutions in these chromosomes’ strings [2]. The different aspects of each solution are positioned into the slots which form the string [3]. A new set of solutions are found by the crossover between two strings (parent strings), and the new strings (children) will inherit the best features of the parent strings.
\nIn construction-related fields, GA has been applied in many multi-objective optimization problems. For example:
GA was used to improve sustainability in housing units. Karatas and El-Rayes [4] used GA in a single-family housing unit to optimize operational environmental performance, social quality of life, and life cycle cost. They used 33 decision variables in the model and computed in 47.5 hours 210 near-optimal solutions within a large search space of configurations and decisions (more than 2.6 quadrillion).
GA was used to solve conflicting objectives in construction scheduling. For instance, Agrama [5] used GA to optimize building schedules. The author analyzed a 5-storey building and used nine scenarios for the weights of three objectives: project duration, total actual crews, and total interruptions for all activities. The model was implemented in Excel (Evolver) and solved by GA. In addition, it was found that the model performs consistently and can be used with both the critical path and line of balance methods. Moreover, the results obtained were identical to those in the literature but required less time and effort. Alternatively, Aziz et al. [6] introduced a method that combines CPM with GA to optimize the utilization of resources for mega construction projects in terms of time, cost, and quality. An 18-activity schedule was tested using the proposed method. To avoid complexity, the five decision variables which were construction materials, crew formation, crew overtime policy, machinery efficiency, and contractor class were all combined into a single decision variable called resource utilization. In this test, 305 optimal solutions were identified. Additionally, the results showed that the model outperformed the approach used by Feng et al. [7] with the same case example.
GA was used in managing site operations. For example, in material logistics, Said and El-Rayes [8] presented an example of a 10-storey building consisting of 107 activities with four temporary facilities. The aim of the model was to minimize total construction logistics costs (Eq. (1)) and minimize project schedule criticality (Eq. (2)).
where,
Because the search space is large and the problem is complex, the authors justified the use of a GA model that involves 152 decision variables and 462 constraints. The model generated 361 optimal solutions. For equipment management problems, Xu et al. [9] proposed dynamic programming-based GA because they believed it would be capable of solving this type of problem more efficiently than traditional methods. The goal of the method was to minimize the project’s total cost and maximize equipment operations such that in case of equipment failure there would be an equipment available. Moreover, to make the method more reliable, the failure rate of the equipment was considered a fuzzy variable. An actual hydropower project in China was selected to test the model. Under the same environment, the proposed algorithm performed better in searching than the standard GA.
\nIn summary, there is evidence that GA can optimize different objectives in the construction industry in the field of scheduling, sustainability, and site operation.
\nThe DE approach is efficient and has low algorithmic complexity. There is also some evidence of its effectiveness in tackling problems of continuous optimization with different types of constraints and functions [10]. The members of the population in DE use floating-points which identify each member’s direction and distance [11]. Therefore, the main concept behind the DE approach is that it creates a new population member with a vector that has the difference between two members’ vectors; that process is done by the mutation and crossover processes [12].
\nDE has proved its effectiveness in complex planning and scheduling problems by optimizing cost and time in addition to quality, environmental impact, or resources. For example:
Narayanan and Suribabu [13] applied DE to assist contractors in optimizing their plans for subcontracting in terms of cost, time and quality. To examine the model, they used a 7-activity and an 18-activity project. By comparison, the DE model generated better solutions than ant colony optimization (ACO) for cost in the first case, and for cost and time in the second case.
Alternatively, Cheng and Tran [14] used a two-phase DE model on a 37-activity warehouse project to minimize total project cost and duration, while accounting for resource constraints. In the first phase, a multiple objective DE model was used to find the optimal tradeoff between time and cost in construction activities. Based on the solution obtained in the first phase, the best schedule was found within resource constraints in the second phase. A comparison of the results showed that the developed model outperformed three evolutionary algorithms: DE, particle swarm optimization (PSO) and NSGA-II.
Subsequently, Cheng and Tran [15] proposed opposition-based multi-objective DE. The aim was to optimize construction products in terms of cost, time and environmental impact. The model used opposition-based learning to increase precision and convergence speed. A tunnel project consisting of 25 activities was used to test the model. The proposed model was superior compared to NSGA-II, PSO, and DE algorithms. The exact approach also outperformed these algorithms in a similar study conducted by Cheng and Tran [16].
The goal of the Cheng and Tran [16] study was to minimize project time (Eq. (3)), project cost (Eq. (4)), and the utilization of resources (Eqs. (5) and (6)) in overtime shifts.
where in Eq. (3), \n
A 15-activity and a 60-activity project were used to test the model. In just one run, the model was capable of finding Pareto-optimal solutions to solve the objectives of the problem.
\nIt can be concluded that the DE algorithm is capable of optimizing several objectives of time, cost, resource utilization, and environmental impact. Moreover, as DE and its variations successfully optimized those objectives, they also surpassed ACO, PSO, and NSGA-II in construction scheduling optimization.
\nSPEA works by archiving the non-dominated solutions found in the Pareto-front at every iteration. Then, based on the number of solutions it dominates, each solution in the archive is ranked with a strength rate [10, 17].
\nIn dealing with scheduling problems, SPEA was proposed by Elazouni and Abido [18] to optimize the three conflicting objectives of maximizing profit and minimizing required finance and resource idle days. The study used two examples from the literature to test the efficiency and scalability of the model. In the first example, the model was tested for its effectiveness in solving a 9-activity project. The model confirmed its robustness by achieving 50 identical solutions. By searching these solutions using a fuzzy based method, the top ones were selected. In the second example, an 18-activity project was used to assess the model’s scalability. Four solutions (maximum profit, minimum finance, minimum resource idle days, and the top compromised solution) were drawn from the 48 solutions obtained in the Pareto-optimal front. Clustering the Pareto solutions set was used to keep it within a manageable size. Nevertheless, because of the clustering, this method may result in the loss of some extreme Pareto solutions.
\nBy optimizing the construction objectives of profit and resources, SPEA has verified its efficiency in the scheduling field. However, the clustering method proposed by Elazouni and Abido [18] should be avoided when using SPEA in order to avoid the elimination of some extreme Pareto solutions. New clustering approaches should be explored in upcoming studies.
\nOne of the most powerful tools of genetic algorithms is NSGA-II. It uses the non-dominated sorting for the solutions in the population. The non-dominated solutions are ranked at every iteration, and are excluded from the population in every iteration afterwards. In addition, in each ranked-solution set, the solutions are compared to each other by their crowding formation. In the crowding step, the position of a single solution is measured by its distance from the adjacent solutions’ points, and based on its distance, the solution is assigned with a rank, as the best ranks start from the shortest distance to the longest one [10].
\nNSGA-II has been used to solve multi-objective problems aimed at the optimality of energy consumption and sustainability in buildings. For instance:
Eliades et al. [19] used NSGA-II to optimally select the installation locations for indoor air quality sensors, in terms of number of sensors, and average and worst-case impact damage while considering the building’s usage in the parameters. A simple 5-room building and a 14-room house were studied to illustrate the performance of the proposed model, with 5 and 2310 contamination scenarios, respectively. Grid and random sampling were used to construct the contamination scenarios, and the multi-zone building program CONTAM simulated them.
In zero-energy-building (ZEB), Hamdy et al. [20] used a modified version of NSGA-II to find solutions for the optimal cost and nearly zero energy building performance with respect to the guidelines of European directives for the energy performance of buildings. Due to the large number of combinations, the solution space was divided into three stages. The total number of combinations (179, 712) in the first stage were searched in 800 runs.
Huws and Jankovic [21] took into account future weather changes that could affect retrofitting strategies. These weather changes may eventually unsettle the performance of zero-carbon buildings by increasing the carbon emissions or cost, or in some cases a combination of these may create thermal discomfort. For that reason and to achieve optimal solutions for retrofit, environmental, social, and economic constraints were considered in optimizing the objectives of minimizing cost, CO2, and thermal discomfort. A simple 60 m2 box model was created using the DesignBuilder program. DesignBuilder and JEPlus were used to perform the optimization process. NSGA-II within JEPlus was used for its capability of searching a large solutions space, and to avoid being stuck in a local suboptimum. The results indicated that there is an applicable alternative for both current and future weather.
In sustainability for low-income housing, Marzouk and Metawie [22] incorporated NSGA-II with BIM to assist the Egyptian government find solutions that best optimize those objectives. The BIM model was created using Revit. The model was defined based on the quantities and properties of the materials extracted from the BIM model. These quantities helped to find the different solutions in terms of project cost, duration and maximum LEED points. Construction productivity and cost were determined using a 44-activitiy low-income housing building. Moreover, LEED points were calculated through five credits chosen from the materials and resources category.
Kasinalis et al. [23] studied the improvement of indoor environment while reducing the energy consumption in climate adaptive building shells, and quantified the impact of using seasonal adaptation façade on those objectives. The example of an office zone model was used to evaluate the approach. The combination of daylight and energy simulations were utilized with NSGA-II to perform multi-objective optimization on that example. The optimization process considered six design parameters for the façade. The results showed that using a seasonal adaptation façade with these parameters is more efficient than a non-adaptive façade, since it can save up to 18% of energy consumption and enhance the quality of the indoor environment.
Inyim et al. [24] approached the problem of building components and material selection by using (SimulEICon) a BIM tool that simulates the environmental impact in buildings. The optimization process of time, cost and CO2 emissions was performed by NSGA-II. The case study was an actual zero net energy house. The model considered 16 activities and 185 building components. It was found that some of the combinations of components suggested by SimulEICon matched the original component combinations used in the existing house. However, SimulEICon lacked the ability to account for more than three objectives.
Carreras et al. [25] introduced an approach for selecting the thickness of insulation material for building shells. The objective of the study was to select the best option for the insulation that optimizes the costs (Eq. (7)) and environmental impacts (Eq. (8)) associated with energy consumption.
where
The authors used the example of a cubicle without insulation to compare the different results collected from using two cases of insulation. In the first case, similar thicknesses were used over the cubicle, while in the second case, different thicknesses were considered. Three materials were considered in the insulation selection process (polyurethane, mineral wool, and polystyrene). From the results, the polyurethane insulation was the least costly solution, whereas the optimal environmental impact solution was mineral wool insulation. The proposed methodology could improve the costs and environmental impacts by almost 40% when compared to a non-insulated cubicle.
\nSite operations and planning problems were also tackled using NSGA-II. For instance:
Fallah-Mehdipour et al. [26] applied NSGA-II to solve two tradeoff problems, time-cost and time-cost-quality, respectively. To validate the proposed method, an 18-activity and a 7-activity work schedule were utilized. Additionally, multi-objective PSO was applied. The results showed that NSGA-II was superior to multi-objective PSO.
In managing and storing materials in a construction site, Said and El-Rayes [27] presented an automated module, which imports its data from BIM files and historical schedule data. A module in the system was named construction logistics planning (CLP) and aimed to minimize the cost of logistics and the criticality of the schedule. These objectives were optimized by tackling four decision variables using NSGA-II. An application model of a 10-storey building project was used to apply the optimization process. The automated system generated better results compared to using CLP alone. A total of 361 optimal solutions were produced within 65 hours. Unlike CLP, which considered the utilization of exterior site space and disregarded the interior one, the system generated the solutions accounting for both spaces.
In site operations, Parente et al. [28] proposed NSGA-II to optimize the allocation of compaction equipment within the criteria of cost and time associated with earthworks in large infrastructure projects. Additionally, linear programming was used for the allocation of the remaining equipment such as trucks and excavators. The proposed method which uses an actual construction site as a case study proved to be superior to the S-metric selection evolutionary algorithm as well as manual allocation.
NSGA-II was used to find solutions in problems involving upgrade plans for water networks and slum areas. For example:
Creaco et al. [29] divided the construction phases of a water network upgrade into four phases, considering the different phases of upgrades to the water network in a 100-year plan of possible upgrades. NSGA-II was used with a model of six network nodes and eight pipe laying locations to find the optimal solutions within the two objective functions: maximizing the minimum pressure and minimizing the cost, while the pipe diameters are acting as the decision variables. The proposed approach provided better results than the studies that used single phasing, by giving the optimal solution for maintaining the water distribution and pressure quality through the time of upgrade phases. In a similar study, Creaco et al. [30] proposed the use of NSGA-II while considering an additional factor to the study, which was the uncertainty of water demand. The authors determined the uncertainty using a probabilistic approach. Based on an example with 26 network nodes and 31 pipe laying locations. The probabilistic approach was compared with the deterministic approach used by Creaco et al. [29]. The results revealed that the solutions obtained by the probabilistic approach had higher costs than the solutions of the deterministic approach, especially in the first phase. However, the probabilistic solutions generated better results in terms of costs when the comparison was about the worst-case scenario.
In uneven ground levels of slum areas, El-Anwar and Abdel Aziz [31] used an example of nine-zone slum area with a population of 2770 families to select the optimal upgrade plan. The optimization process involved three objectives: maximization of benefit of proposed upgrading projects, minimization of costs and socioeconomic disruption for the families. Due to its superiority over other GAs in solving multi-objective problems, NSGA-II was selected to solve the problem in which it generated 2000 solutions in less than 1 minute. Nevertheless, the time schedules module was not included in the model hence affecting its robustness.
Brownlee and Wright [32] analyzed the relationship between design objectives and the effectiveness of design variables on the design objectives by using NSGA-II. They sorted the objectives by simple ranking. The approach was performed on a five-zone building with only two design objectives. The objectives to be minimized were total annual energy use and capital cost, and the design variables were 52 in total. Forty-nine solutions were generated using NSGA-II. However, the proposed approach failed to discriminate the distance variables which are the variables that measure the sets from the true Pareto-optimal set from the floating variables which are the variables that have no effect on the objective function.
As the above-cited studies show, the NSGA-II proved its capability in optimizing for scheduling, urban planning, infrastructure, sustainability, energy and environmental design, and resource management. In addition to its superiority over other GAs, NSGA-II has also outperformed other methods in some fields. One of those is the multi-objective PSO applied to scheduling problems.
\nThe tournament selection among a population’s individuals and Pareto dominance are the two basic ideas of NPGA’s process. The selection process is based on the dominance of two randomly selected individuals from the population. To determine which individual of these two is dominant over the other, another set of individuals are picked and used to go against the two competing individuals, to examine the level of the two competing individuals in dominating each individual of the set. The winning criterion is defined by Pareto-front dominance. Therefore, one of the two competing individuals is selected if the other is dominated by one of the individuals in the set [33, 34].
\nKim et al. [35] used NPGA to optimize cost, time and resource utilization. They optimized the three objectives at the same time. To test the performance of the method, they conducted two case studies. The first case had 11 activities, and measured the method’s efficiency in solving the tradeoff problem between cost and time. In addition to the objectives in the first case, the second case extended the examination of the approach by including the resource-leveling index as an objective. The results showed that this method could provide decision makers with different solutions to enable them selecting the one that meets their preferences.
\nMOGA is an advanced version of traditional GA. The difference between MOGA and GA is the individual fitness assignment, while the remaining steps are followed as in GA. In MOGA, ranking is assigned for each individual in the population. The rank is assigned based on individual’s dominance, if the individual is not dominated by another individual in the population then it is assigned with the rank of one. But if an individual is dominated by other individuals then it is assigned with a rank corresponding to the total number of dominating individuals plus one [36].
MOGA has shown its capabilities in achieving optimal structural design. For example, Richardson et al. [37] tackled the design problem of an x-bracing structural system for a building façade. Minimizing the cost of the bracing connections and the effectiveness of the bracings were the objectives under the multi-objective topology optimization process (Eq. (9)).
where
where
While the constraints change as the design progresses, the proposed approach dynamically adapts to those constraints. Museum façades were picked to test the performance of the optimization method.
In reducing the energy consumed and environmental impact in buildings, Baglivo et al. [38] have used an improved version of MOGA (MOGA-II) on combinations of sustainable building materials for external walls of zero energy buildings, to achieve the best optimal solutions in balancing the life cycle cost and energy consumption. The materials were tested according to their thermal characteristics based on the Mediterranean climate. The assessment of material combinations was carried on six thermal-related objectives. The study concluded that the best selection of materials for external walls was by placing the insulation coating on the external side of the wall, while placing the high internal capacity material on the interior side. Similarly, Baglivo et al. [39] have conducted a study that added one more objective to the same six objectives.
The pattern of flocking birds and fish was the inspiration of PSO. In PSO, a set of solutions is called swarm, while a solution is called particle [26]. The particles are positioned in a D-dimensional search space. In each step, every particle changes its velocity to move toward the best solution and toward the global best solution [40].
\nDifferent issues of construction engineering and management were tackled by PSO. Some studies proposed PSO to solve site planning problems. For instance:
Xu and Li [41] proposed permutation-based PSO to solve the planning problem of a dynamic construction site layout, in which ordinal numbers assigned to the particles were used to present the potential solutions. The objectives considered in the problem were the layout cost and the environmental and safety accidents. Since the study accounted for uncertainty, fuzzy random variables were included in the model. The model used the example of 14 temporary facilities in a hydropower project to evaluate its efficiency. The proposed approach proved to be more realistic than existing traditional approaches.
Xu and Song [42] approached the problem of unequal-area departments in dynamic temporary facility layout using position-based adaptive PSO. By using the facilities’ coordinates as base for its model, the optimization process aimed at minimizing the total distance between adjacent facilities and the resulting costs associated with rearrangement and transportation, in which the transportation costs were considered as fuzzy random variables. The modified PSO was evaluated through a case study of a large-scale hydropower construction project. The proposed method showed better performance in obtaining optimal solutions when compared to standard PSO and GA.
Li et al. [43] proposed a modified PSO to achieve optimal solutions for dynamic construction site layout and security planning. The study approached the problem using the Stackelberg Game theory, in which the construction manager (the leader) must set up the layout and secure the facilities, then the attacker (the follower) has to create the maximum possible economic damage to the facilities. Bi-level multi-objective PSO was proposed to solve the problem. The method was implemented in a hydropower construction project to test its performance. The proposed method outperformed GA in achieving optimal solutions.
PSO has also been used in tackling different objectives in the maintenance of deteriorating structures. For example:
Yang et al. [44] approached the problem of life cycle maintenance planning for deteriorating bridges using PSO with Monte Carlo simulation (MCS). Cost, safety and condition levels were the main objectives in the maintenance problem. Uncertainties in the maintenance cost, work effects of maintenance, and the structure’ deterioration rate were also accounted for in the study. Parallel programming was used to minimize the computing time to solve the problem. Yang et al. [44] considered three paradigms in the programming process, namely master-slave, island, and diffusion. In each paradigm, the computers have a different set up to run MCS in parallel. From the analysis, the island paradigm surpassed the other two in terms of solution quality. By comparison, the multi-objective PSO algorithm outperformed NSGA-II.
Chiu and Lin [45] proposed PSO to achieve the optimal strategies in maintaining reinforced concrete buildings. The authors considered five objectives in the study, which are life cycle cost, failure possibility, spalling possibility, maintenance rationality, and maintenance times. Assessment models of probabilistic effects were employed to observe the effects of maintenance strategies on the damage index. The four processes of analysis of deterioration, assessment of seismic performance, forming maintenance strategies, and multi-objective optimization were performed in the proposed maintenance strategy. The evaluation was completed using a case study of a four-story reinforced concrete school building.
Some researchers used PSO to tackle different design objectives and constraints to achieve optimal sustainable design solutions. For instance:
Decker et al. [46] have proposed a PSO algorithm to reach better design solutions in timber buildings. In addition to architectural, energy and environmental constraints, the study added structural constraints. The optimization process was in terms of energy needs, thermal discomfort, floor vibration, CO2 emissions, and embodied energy. To minimize computing time, the simulation model was transformed using a metamodeling procedure. A three-story office building was used as a case study to validate the proposed approach.
Chou and Le [47] used PSO in combination with MCS to attain the optimal solutions for building designs in terms of minimizing duration (Eq. (12)), cost (Eq. (13)), and CO2 emissions (Eq. (14)).
where
In addition to PSO, a probabilistic method was applied to handle the uncertainties associated with the objectives of the study. The case study of a 12-activity roadway pavement project was used to evaluate the performance of the proposed method.
\nIn sum, PSO proved its effectiveness in tackling the multi-objective optimization problems in different construction engineering and management areas such as site planning, maintenance of a structure, and sustainability issues. It was found that PSO’s performance was superior compared to traditional approaches such as GA and advanced approaches such as NSGA-II.
\nThe stimulus in discovering the ACO algorithm was the movement of ants and their trails of pheromones when searching for food. In the ACO process, each solution is connected to a route that is searched by an ant. Each solution’s quality is evaluated by the quantity of pheromones that were deposited on the route by ants. The amount of pheromone left on a route indicates the closeness to the optimal solution. The chance of finding the shortest route increases for an ant as the amount of pheromone on a route increases [48].
\nThe proximity and number of construction facilities and other resources on a construction site could contribute to an increase in cost and safety issues. Ning and Lam [49] developed a modified ACO model to tackle safety and cost problems within a site layout of irregular shape. The model was aimed to minimizing safety/environmental concerns by reducing the occurrence of accidents (Eq. (15)) as well as minimizing the total handling cost between facilities by reducing the cost associated with resource exchanges among facilities (Eq. (16)).
\nwhere
The optimization process started by dividing the site layout into a grid. The grid units were selected based upon the dimensions of the facilities. Then, the ACO model was used to assign the different facilities on the site grid. To test the soundness of the model, a residential project composed of four buildings was selected. The proposed grid strategy reduced the complexity of the computational process.
\nLike the analytic hierarchy process, decision makers utilize ANP to solve multi-criteria decision problems. The AHP uses a one-way top-down hierarchal process for its components such as goals, criteria, and alternatives [50]. The ANP which is a generalized version of AHP uses a network for some problems when their components have interdependencies between them. The flow in the ANP’s network is open and allows any component to interact with another regardless of their levels, which is not possible in AHP [51].
\nLiang and Wey [52] proposed an ANP model to optimally select government projects by accounting for the limitation of resources along with uncertainties and socioeconomic factors. In order to test the model’s effectiveness, seven projects in a nation-wide highway improvement project were used as an example. In the example, construction costs were determined by probability distributions and seven criteria were used to evaluate the projects. Moreover, since the model involves the use of multiple criteria, ANP was combined with MCS to make the selection of projects based on the solutions achieved by solving the multi-objective problems. ANP ranking was used to rank each project based on its value of priority among other projects. A cost-benefit approach was used to optimize the selection of projects based on the existing budget plan and the allocation of remaining budget to fund a project in full. The four objectives within these two problems were minimization of cost (Eq. (17)) and the number of project managers (Eq. (18)), and the maximization of project ranking (Eq. (19)) and the number of completed projects (Eq. (20)).
\nwhere
The SFLA idea is based on frogs’ behavior in their search to locate the largest quantities of food [53]. A single solution is represented by one frog [54, 55]. The frogs are divided into groups (memeplexes). Each memeplex of frogs performs a local search, and every frog has an idea which is affected by other frogs’ ideas to improve the quality of the local search [56]. A shuffling process is performed to allow the memeplexes in exchanging information between them and create new memeplexes to ultimately improve their quality of search [53, 54, 56].
\nImproving the quality of the final product with limited resources is the ultimate goal of construction managers and planners. Time, cost, and resources play important roles in achieving this goal. Ashuri and Tavakolan [57] concurrently optimized three objectives: the duration expressed by sum of the durations of activities on the critical path, the project cost including direct and indirect costs, and resource allocation variations expressed in Eq. (21).
\nwhere
To solve these problems, they used the SFLA model. In order to find feasible solutions to the problem at hand, the model accounts for the reallocation of resources and for activity interruptions and splitting. In addition, the authors made use of the advantages of PSO and the shuffling complex evolution algorithm, which helped the model achieve better solutions and converge more rapidly. A 7-activity and an 18-activity project were utilized to assess the efficiency of the model. Delphi was the coding environment for the model. Due to the complexity of the problem, the solutions obtained were near-optimal. However, the proposed model generated better solutions than other algorithms used prior to the study.
\nSA inherits its method from the movements of atoms within a material during the process of heating and then slowly cooling down [58]. In the optimization problem, the physical system’s characteristics resemble the actual annealing process [10]. Talbi [10] listed the characteristics of physical annealing with their corresponding characteristics of the optimization problem. In physical annealing, temperature and speed of cooling down play important roles on the strength of metals. Deficiencies (metastable states) occur when cooling down speed is fast or the temperature at the start is not high enough [59]. That means carefully setting up the temperature and cooling down speed is essential in escaping the local optimum—metastable state in physical annealing—and reaching the global optimum. A solution that is generated after an iteration is used, if feasible, to generate a new solution, but if the solution is infeasible, it is accepted only if it meets the probability criterion [10, 60]. The probability increases in obtaining an optimal or near-optimal solution when the annealing is slowed down [61].
\nTo optimally design and construct a water distribution network, Marques et al. [62] proposed a model that used the SA algorithm combined with the EPANET hydraulic simulator. The objective was to minimize the cost of construction and operation including the initial and future costs, and to minimize violations in pressure as expressed in Eq. (22).
\nwhere
Eight scenarios were accounted for varying between three possible patterns of growth in the area: expansion, no expansion, and depopulation in a 60-year period. They split the 60-year duration of the plan into 320-year stages, and structured them into a decision tree to show the probability of the paths in each scenario. They used a 17-node distribution network to illustrate the model’s efficiency. The decision variables included cost, diameters of pipes (eight diameters were considered), and carbon emissions produced during construction and operation (in terms of tons). The value of the objective function was not noticeably affected by the decision variable of carbon emission costs.
\nThe PGSA imitates the growth process of trees. The model’s formulation for the optimization process in PGSA is based on the growth of plants [63]. It begins at the root then moves toward the light source (global optimum solution) to grow the branches [64]. A probability model is employed to form new branches which are used to guide the objective function toward the optimal solution [65].
\nTo better minimize the losses and costs caused by an attack to the construction site and to increase the safety precautions to counter these attacks, Li et al. [66] used a bi-level model. The objectives of reducing attack-related cost and increasing facility productivity were considered at the upper level, in which the secured facilities were constrained by cost. The attacker, on the other hand, has the objective of reducing facility productivity, which is considered in the lower level. The formulation of the objective functions is as follows:
\nwhere
where
Because integer programming made the problem complicated, the authors proposed PGSA. The model was applied on an actual hydropower project. Fifty runs were executed to achieve the optimal solution in less than 4 minutes. Even though the proposed model efficiently solved the problem, it did not top the list of algorithms. This study was the first study to apply PGSA on the problem of construction site security.
\nThe Hungarian algorithm is a modified form of the primal-dual algorithm that is used to solve network flows. In assignment problems, the Hungarian algorithm changes the weights in a matrix to locate the optimal assignment. Eventually, a new matrix is obtained in which the optimal assignment is identified [67].
\nEl-Anwar and Chen [68] proposed a modified Hungarian algorithm to solve post-disaster temporary housing problems. They considered the problem as an integer problem. An earthquake simulation example was used to examine the model’s efficiency. The number of decision variables was determined by multiplying the housing alternatives (178) with the number displaced families (5000). Throughout the 13 temporary housing problems, a varying number of decision variables were considered. In terms of the running time, the Hungarian algorithm has shown superiority over integer programming. In the example, the running time for integer programming increased exponentially as the number of decision variables increased, and ran out of memory in case more than 24,000 decision variables were used. The Hungarian algorithm, on the other hand, solved all the problems with the maximum number of decision variables (890,000).
\nMINLP is an optimization problem in which the variables are constrained to continuous (e.g., costs, dimensions, mass, etc.) and integer values (typically binary 0 and 1), and the solution space and the objective functions are represented by nonlinear functions [69, 70, 71]. To solve complex problems that involve nonlinearity and mixed-integers, MINLP utilizes the combination of mixed-integer programming (MIP) and nonlinear programming (NLP) [72]. Thus, in solving MINLP problems, the approach is not considered a direct problem solver. The methods used to solve MINLP optimization problems include: branch and bound method, benders decomposition, and outer approximation algorithm [73].
Fan and Xia [74] used MINLP to reduce energy consumption in residential buildings. The objectives of the study were to increase the energy savings and economic benefits within budget limitations. The example of a 69-year old house was used to test the model, in which the retrofitting plan included the insulation materials for the roof and external walls, windows, and the installation of solar panels. The model proved to be effective in minimizing the energy consumed by the building; from the results obtained, in a 10-year period, the house could save around 288.44 MWh.
Karmellos et al. [75] also used MINLP to optimize the energy used by a building. The minimization of energy consumption every year and the cost of investments were the two main objectives in the optimization process. To test the model’s soundness, the energy consumption in two houses was investigated. The first case involved a new house located in the UK while the second case was an existing house located in Greece. Fifty-four decision variables were accounted for in the model, which represented different building components including electrical appliances, building envelope, and lighting and energy systems. The model was effective in solving the optimization problem of and building energy. It was found that energy consumption goes down when investments in energy efficiency are increased.
One way in approaching complex optimization problems is to combine two or more techniques together in order to overcome the deficiencies that one or some of them may possess. This approach could affect the overall quality of the solution in an optimization problem. The hybridization of methods has shown its efficacy in accomplishing optimization quality in construction. Hybrid methods have different operational characteristics in tackling optimization problems. While some hybrid methods work by carrying the entire solution process as a single novel technique, others work in tandem whereby one method works on some steps of the solution process and the other steps are completed by another method.
\nNSGA-II was hybridized with other approaches to solve optimization problems in construction planning, scheduling, energy conservation, transportation, and environmental design. For example:
Mungle et al. [76] used fuzzy clustering-based genetic algorithm (FCGA) to find optimal solutions for the trade-off problem of time, cost and quality within the construction tasks. The method hybridized the fuzzy clustering approach with NSGA-II. In addition, AHP was utilized to measure the construction activities’ quality. To evaluate the model’s efficiency, a highway construction project was selected as an example. The authors used the example in three cases with different number of activities, i.e., eighteen, twelve, and seven-activity networks, in which the proposed approach was compared to other methods. The results of the comparison showed that FCGA surpassed MOPSO, MOGA and SPEA-II in terms of diversity as well as the speed and degree of convergence.
Monghasemi et al. [77] proposed an approach that combines NSGA-II with MOGA to solve a discrete problem of cost, time, and quality in construction project scheduling. An 18-activity highway construction project was used to examine the proposed model. MOGA was utilized to search the large size of 3.6 billion solutions and obtain near true optimal solutions. Shannon’s entropy method was used to assign normalized weights to the three objectives in the obtained solutions. These weights were used to rank the solutions by performing the evidential reasoning method, which assist decision makers in assessing each solution in terms of performance.
Brownlee and Wright [78] proposed modified approaches of NSGA-II on a simulation-based optimization problem for building energy. The minimization of energy usage and construction cost were the two objectives in the optimization process. The aim of the study was to find an approach that surpasses the basic NSGA-II in terms of convergence rate and solution quality. The study used a middle floor from a commercial office building in three different cities to test the proposed model. The authors merged NSGA-II with two other approaches, namely radial basis function networks and deterministic infeasibility sorting. These approaches enabled the model to prevent the elimination of infeasible solutions and to keep them in the population. The objectives were represented by 50 decision variables (30 continuous, 8 integers and 12 categorical) and 18 inequality constraints. Moreover, the optimization runs were limited to 5000 completed within almost a day by six parallel simulations. The model was found superior to the basic NSGA-II in two of the three building examples.
Xu et al. [79] proposed a multi-objective bi-level PSO (MOBLPSO) to optimize the minimum cost network flow of construction material transportation in terms of duration and cost. In the upper level of the model, the time to transport materials in addition to direct costs were minimized by the contractor by selecting the most convenient routes for transporting materials. Depending on the decisions made in the model’s upper level, every transporter’s flow of material in those routes were considered by the transportation manager to reduce the costs of transportation. Because of the complexity of the problem the PSO approach was hybridized with two other methods, one in each level. In the upper level, PSO was integrated with Pareto Archived Evolution Strategy (PAES) to keep the best position for the solutions up to date. In the lower level, PSO used passive congregation to prevent the convergence from happening too early. The case of an actual hydropower construction project was utilized to examine the model’s soundness. The model outperformed multi-objective bi-level genetic algorithms (MOBLGA) and the multi-objective bi-level simulated annealing algorithm (MOBLSA).
Xu et al. [80] conducted a similar study to the one mentioned above, but in this study the cost and duration of transportation were considered as fuzzy random variables. A fuzzy random simulation-based constraint checking procedure was coupled with MOBLPSO to solve the transportation assignment problem which was used to control the flow of materials within a given period. The road network of an existing hydropower project was used for the evaluation of the model. With accounting for uncertainties, the model showed its efficiency and capability of solving the transportation problem.
Zhang et al. [81] proposed immune genetic PSO (IGPSO) which couples immune genetic algorithm with PSO. The approach was used to tackle the trade-off problem of time-cost-quality in construction, and accounting for bonus and penalty. The hybrid method in the research obtained its characteristics from three methods: (1) from the immune algorithm, whereby the hybrid method inherits the immune selection and the memory recognition; (2) from the genetic algorithm, which implements mutation and crossover; and (3) by limiting the particles’ maximum velocity using the constriction factor in PSO, which speeds up the convergence in initial steps. In addition, the study used a PERT network instead of CPM for the schedule. The model was applied on the 19 activities of a three-floor office building, and proved its effectiveness in solving the trade-off problem.
In the trade-off problem, some researchers used the double-loop technique, in which the internal loop executes the simulation, while the external loop carries out the optimization process. However, this technique uses MCS and can sometimes take days to finish the process. Therefore, Yang et al. [82] proposed a procedure that combines the double-loop into one, and used MCS and support vector regression (SVR) with PSO to expedite the process of obtaining optimal solutions for the time-cost trade-off problem. MCS was set to assess the initial solutions’ objective values, and a decision function gained by SVR promptly assesses the solutions obtained by PSO for their objective values. SVR’s direct assessment contributed in shortening the search time of MCS. To test the model, an 18-activity project was utilized as an example. The results obtained showed that the proposed method was superior compared to the methods that used the double loop.
Futrell et al. [83] used PSO coupled with Hooke Jeeves and the generic optimization program (GenOpt) to optimize the performance of daylighting and thermal systems in buildings. Hooke Jeeves was utilized to fine-tune the best solution found in the PSO algorithm by locally searching it. The case study of a classroom design was utilized to evaluate the proposed approach. The classroom was tested on windows facing north, south, west, and east. It was found that there was no significant conflict between the optimization objectives when the windows were facing south, west, or east, but there was a significant conflict between those objectives in the case of windows facing north.
Yahya and Saka [84] used multi-objective artificial bee colony (ABC) with the Levy flights algorithm to find the ideal layout for a construction site. Levy flight which uses a random walk pattern searches food locations found by ABC to locate new solutions. The objective functions of the study were the reduction of the facilities’ total handling cost, and minimization of environmental and safety risks. Two practical study cases were used to assess the proposed model. The first case was a residential project consisting of four high-rise buildings, and the second case was a three-floor private hospital. The first case which was a dynamic site layout was taken from Ning et al.’s [85] study, in which they applied a modified ACO. From the results, the model succeeded in optimizing the site layout problems. By comparison, the method proposed by Yahya and Saka [84] surpassed the plain-ABC and the modified ACO used by Ning et al. [85].
Tran et al. [86] tackled the trade-off problem of time, cost, and quality using the combination of multi-objective ABC with DE. DE was included to use its crossover mutation operators to optimize the stages of exploration and exploitation. A study case of a construction project consisting of 60 activities was used to test the model. The result proved the model’s efficacy in the trade-off problem. The approach was also compared against four other approaches that were used to solve the trade-off problem. The proposed method outperformed multi-objective ABC, multi-objective DE, multi-objective PSO, and NSGA-II.
Marzouk et al. [87] presented a hybrid approach that combined ACO with system dynamics to optimize the selection of sustainable materials. The aim of the study was the maximization of LEED credits and the minimization of cost. The authors employed a study case of a two-floor residential building to validate the efficacy of the model. From the achieved results, the model proved its capability in accomplishing the two objectives of the problem.
In building maintenance planning, Wang and Xia [88] used a predictive control model and DE algorithm to achieve the optimal retrofitting plan that lowers energy consumption. The study’s first objective aimed at increasing a project’s internal rate of return. The study’s second objective was to increase energy savings while accounting for the sustainability period. The authors tackled the optimization of the maintenance plan in two instances. They started by solving the optimization problem without the assumption of uncertainties. They then solved the problem with uncertainties, in which the predictive control model was utilized. To check the approach’s validity, a case study that involved the retrofitting of an office building consisting of 50 stories was considered. The results showed that the proposed approach was effective in finding the optimal maintenance plan.
The complexity of the problems in construction projects makes objective optimization usually difficult using a single approach. Hybrid techniques are effective and useful in generating optimal solutions in complex optimization problems. In some studies, these hybrid methods have outperformed some methods in their basic and variant forms. In scheduling for example, they were superior to multi-objective PSO, multi-objective ABC, multi-objective DE, MOGA, SPEA-II, and NSGA-II. In material logistics, they surpassed multi-objective bi-level GA and multi-objective bi-level SA. In site planning, they outperformed the basic form of ABC and one of the ACO variants. Finally, in sustainability, they were superior to NSGA-II.
\nThis review included 55 papers that were published in refereed journals and conference proceedings published in the years 2012–2016. The authors of these papers conducted studies using various multi-objective optimization methods in the construction industry. There were 16 methods used in these studies in which some of the authors justify their picks on multiple factors (e.g., construction project type, project size, number of objectives, number of constraints, convergence rate, problem complexity such as constraints’ nonlinearity with discontinuity and continuity, etc.). Moreover, some methods were found to be more efficient than others in some studies. For example, in water network planning, Creaco et al. [30] showed that their NSGA-II using a probabilistic approach was superior to NSGA-II used by Creaco et al. [29] in an earlier study in which they used a deterministic approach. The GA proposed by Aziz et al. [6] in a scheduling problem outperformed the GA utilized by Feng et al. [7] for the same case study. Fallah-Mehdipour et al. [26] concluded that NSGA-II has performed better than multi-objective PSO in solving a scheduling problem. Most of the time, it is difficult to guarantee the performance of a method until it is compared with another method.
\nThe most common number of objectives used in the literature is two and three. As expected, cost and duration were the most targeted objectives as cost and duration are important objectives for all construction practitioners. The quality objective has also drawn the interest of researchers as they sometimes include it in trade-off problems with cost and/or duration. However, quality has not been optimized in any other set of objectives than three-objective optimization problems. The energy and environment category is an important candidate in the optimization process, as it came after cost and duration objectives based on the number of times it was optimized. That may be the result of efforts to optimally construct sustainable buildings and lower the depletion of natural resources.
\nAmong the multi-objective methods used in the literature, NSGA-II was the most used method. NSGA-II has proven its capability in solving optimization problems in different fields of construction. In addition to its popularity among researchers, NSGA-II has many advantages that make it suitable for many types of optimization problems such as obtaining diverse solutions in Pareto-front, low computational complexity, solving problems that involve nonlinearity and discontinuity.
\n"Open access contributes to scientific excellence and integrity. It opens up research results to wider analysis. It allows research results to be reused for new discoveries. And it enables the multi-disciplinary research that is needed to solve global 21st century problems. Open access connects science with society. It allows the public to engage with research. To go behind the headlines. And look at the scientific evidence. And it enables policy makers to draw on innovative solutions to societal challenges".
\n\nCarlos Moedas, the European Commissioner for Research Science and Innovation at the STM Annual Frankfurt Conference, October 2016.
",metaTitle:"About Open Access",metaDescription:"Open access contributes to scientific excellence and integrity. It opens up research results to wider analysis. It allows research results to be reused for new discoveries. And it enables the multi-disciplinary research that is needed to solve global 21st century problems. Open access connects science with society. It allows the public to engage with research. To go behind the headlines. And look at the scientific evidence. And it enables policy makers to draw on innovative solutions to societal challenges.\n\nCarlos Moedas, the European Commissioner for Research Science and Innovation at the STM Annual Frankfurt Conference, October 2016.",metaKeywords:null,canonicalURL:"about-open-access",contentRaw:'[{"type":"htmlEditorComponent","content":"The Open Access publishing movement started in the early 2000s when academic leaders from around the world participated in the formation of the Budapest Initiative. They developed recommendations for an Open Access publishing process, “which has worked for the past decade to provide the public with unrestricted, free access to scholarly research—much of which is publicly funded. Making the research publicly available to everyone—free of charge and without most copyright and licensing restrictions—will accelerate scientific research efforts and allow authors to reach a larger number of readers” (reference: http://www.budapestopenaccessinitiative.org)
\\n\\nIntechOpen’s co-founders, both scientists themselves, created the company while undertaking research in robotics at Vienna University. Their goal was to spread research freely “for scientists, by scientists’ to the rest of the world via the Open Access publishing model. The company soon became a signatory of the Budapest Initiative, which currently has more than 1000 supporting organizations worldwide, ranging from universities to funders.
\\n\\nAt IntechOpen today, we are still as committed to working with organizations and people who care about scientific discovery, to putting the academic needs of the scientific community first, and to providing an Open Access environment where scientists can maximize their contribution to scientific advancement. By opening up access to the world’s scientific research articles and book chapters, we aim to facilitate greater opportunity for collaboration, scientific discovery and progress. We subscribe wholeheartedly to the Open Access definition:
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The Open Access publishing movement started in the early 2000s when academic leaders from around the world participated in the formation of the Budapest Initiative. They developed recommendations for an Open Access publishing process, “which has worked for the past decade to provide the public with unrestricted, free access to scholarly research—much of which is publicly funded. Making the research publicly available to everyone—free of charge and without most copyright and licensing restrictions—will accelerate scientific research efforts and allow authors to reach a larger number of readers” (reference: http://www.budapestopenaccessinitiative.org)
\n\nIntechOpen’s co-founders, both scientists themselves, created the company while undertaking research in robotics at Vienna University. Their goal was to spread research freely “for scientists, by scientists’ to the rest of the world via the Open Access publishing model. The company soon became a signatory of the Budapest Initiative, which currently has more than 1000 supporting organizations worldwide, ranging from universities to funders.
\n\nAt IntechOpen today, we are still as committed to working with organizations and people who care about scientific discovery, to putting the academic needs of the scientific community first, and to providing an Open Access environment where scientists can maximize their contribution to scientific advancement. By opening up access to the world’s scientific research articles and book chapters, we aim to facilitate greater opportunity for collaboration, scientific discovery and progress. We subscribe wholeheartedly to the Open Access definition:
\n\n“By “open access” to [peer-reviewed research literature], we mean its free availability on the public internet, permitting any users to read, download, copy, distribute, print, search, or link to the full texts of these articles, crawl them for indexing, pass them as data to software, or use them for any other lawful purpose, without financial, legal, or technical barriers other than those inseparable from gaining access to the internet itself. The only constraint on reproduction and distribution, and the only role for copyright in this domain, should be to give authors control over the integrity of their work and the right to be properly acknowledged and cited” (reference: http://www.budapestopenaccessinitiative.org)
\n\nOAI-PMH
\n\nAs a firm believer in the wider dissemination of knowledge, IntechOpen supports the Open Access Initiative Protocol for Metadata Harvesting (OAI-PMH Version 2.0). Read more
\n\nLicense
\n\nBook chapters published in edited volumes are distributed under the Creative Commons Attribution 3.0 Unported License (CC BY 3.0). IntechOpen upholds a very flexible Copyright Policy. There is no copyright transfer to the publisher and Authors retain exclusive copyright to their work. All Monographs/Compacts are distributed under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0). Read more
\n\nPeer Review Policies
\n\nAll scientific works are Peer Reviewed prior to publishing. Read more
\n\nOA Publishing Fees
\n\nThe Open Access publishing model employed by IntechOpen eliminates subscription charges and pay-per-view fees, enabling readers to access research at no cost. In order to sustain operations and keep our publications freely accessible we levy an Open Access Publishing Fee for manuscripts, which helps us cover the costs of editorial work and the production of books. Read more
\n\nDigital Archiving Policy
\n\nIntechOpen is committed to ensuring the long-term preservation and the availability of all scholarly research we publish. We employ a variety of means to enable us to deliver on our commitments to the scientific community. Apart from preservation by the Croatian National Library (for publications prior to April 18, 2018) and the British Library (for publications after April 18, 2018), our entire catalogue is preserved in the CLOCKSS archive.
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\n\nOpen Science refers to doing traditional science with more transparency involved at various stages, for example by openly sharing code and data. It implies a growing set of practices - within different disciplines - aiming at:
\n\nWe aim at improving the quality and availability of scholarly communication by promoting and practicing:
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After finishing his P. hD degree in 1992, he served in the Industry as a Scientific Officer and continued his academic career as a visiting scholar for a number of educational institutions. In 1996 he joined National University of Science & Technology Pakistan (NUST) as an Associate Professor; NUST is one of the top few universities in Pakistan. In 1999 he joined an International Company Lineo Inc, Canada as Manager Compiler Group, where he headed the group for developing Compiler Tool Chain and Porting of Operating Systems for the BLACKfin processor. The processor development was a joint venture by Intel and Analog Devices. In 2002 Lineo Inc., was taken over by another company, so he joined Aalborg University Denmark as an Assistant Professor.\nProfessor Akbar has truly a multi-disciplined career and he continued his legacy and making progress in many areas of his interests both in teaching and research. 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Genomics studies of large populations are producing a huge amount of data, giving rise to computational issues around the storage, transfer, and analysis of the data. Fortunately, cloud computing has recently emerged as a viable option to quickly and easily acquire the computational resources for large-scale NGS data analyses. Some cloud-based applications and resources have been developed specifically to address the computational challenges of working with very large volumes of data generated by NGS technology. In this chapter, we will review some cloud-based systems and solutions for NGS data analysis, discuss the practical hurdles and limitations in cloud computing, including data transfer and security, and share the lessons we learned from the implementation of Rainbow, a cloud-based tool for large-scale genome sequencing data analysis.",book:{id:"5416",slug:"cloud-computing-architecture-and-applications",title:"Cloud Computing",fullTitle:"Cloud Computing - Architecture and Applications"},signatures:"Shanrong Zhao, Kirk Watrous, Chi Zhang and Baohong Zhang",authors:[{id:"176364",title:"Dr.",name:"Shanrong",middleName:null,surname:"Zhao",slug:"shanrong-zhao",fullName:"Shanrong Zhao"}]}],onlineFirstChaptersFilter:{topicId:"9",limit:6,offset:0},onlineFirstChaptersCollection:[{id:"82999",title:"Understanding the Artificial Intelligence Implementation for Allocating an Order to a Seller among Multiple Sellers Who Sell the Same Product",slug:"understanding-the-artificial-intelligence-implementation-for-allocating-an-order-to-a-seller-among-m",totalDownloads:1,totalDimensionsCites:0,doi:"10.5772/intechopen.105560",abstract:"E-commerce sectors are growing rapidly worldwide and it adopts the new technological innovation drastically, such as embracing artificial intelligence in e-commerce sectors. Machine learning adaptation in e-commerce sectors is the most and much news already published by giant e-commerce companies, such as Amazon and eBay. The aim of this paper is to find out how artificial intelligence helps the e-commerce platform to choose a seller from multiple sellers when the same products or listings are sold by multiple sellers. When a customer will place the order, then who will get the order of the customer as multiple sellers sell the item within the same product listings. In the research, it is figured out that machine learning techniques are normally used for the selection of the seller where the prior points used for finding the appropriate seller are feedback or ratings, seller products location or distance from the customer, advertising or PPC or campaign, discounts, etc.",book:{id:"11914",title:"E-service Digital Innovation",coverURL:"https://cdn.intechopen.com/books/images_new/11914.jpg"},signatures:"Md Imtiaz Ahmed"},{id:"83016",title:"Digitization of Traditional Higher Education Touchpoints",slug:"digitization-of-traditional-higher-education-touchpoints",totalDownloads:2,totalDimensionsCites:0,doi:"10.5772/intechopen.105926",abstract:"This chapter presents the possibilities of using e-services in the context of higher education. Modern technologies provide an opportunity to create a stronger bond between the higher education institution and its stakeholders, among whom students and employees are the most important and those who have the greatest needs in terms of the number and frequency of use of e-services. The main objective of this chapter is to explore the role of e-services in relationship management in the higher education complex ecosystem. There is a possibility to digitize a lot of traditional higher education touchpoints, such as everyday administration processes, admission, enrollment, relevant information sharing, e-learning, Q&A, and similar. The comprehensive e-services system was developed and implemented in one of the higher educational institutions. The upcoming generations of students are increasingly likely to have prominent previous experience with the major use of digital technologies as a part of their elementary and secondary level education. Higher education institutions should expand the portfolio of their e-services, given that the demands of students are expected to increase in the future.",book:{id:"11914",title:"E-service Digital Innovation",coverURL:"https://cdn.intechopen.com/books/images_new/11914.jpg"},signatures:"Adam Malešević"},{id:"82995",title:"A Hybrid Genetic, Differential Evolution Optimization Algorithm",slug:"a-hybrid-genetic-differential-evolution-optimization-algorithm",totalDownloads:3,totalDimensionsCites:0,doi:"10.5772/intechopen.106204",abstract:"This chapter presents a heuristic evolutionary optimization algorithm that is loosely based on the principles of evolution and natural genetics. In particular, this chapter describes an evolutionary algorithm that is a hybrid of a genetic algorithm and a differential evolution algorithm. This algorithm uses an elitist, ranking, random selection method, several mutation methods and both two level and three level Taguchi crossover. This algorithm is applied to 13 commonly used global numerical optimization test functions, including a spherical, three hyper-ellipsoid, the sum of different powers, Rastrigin’s, Schwefel’s, Griewank’s, Rosenbrock’s valley, Styblinski-Tang, Ackley’s Path, Price-Rosenbrock, and Eggholder’s functions. This algorithm is applied 1000 times to each of the 13 test functions, and the results shows that this algorithm always converges to each of the 13 test function’s global minimum.",book:{id:"11555",title:"Ubiquitous and Pervasive Computing - New Trends and Opportunities",coverURL:"https://cdn.intechopen.com/books/images_new/11555.jpg"},signatures:"Peter Stubberud"},{id:"82921",title:"A Survey of Lightweight Image Encryption for IoT",slug:"a-survey-of-lightweight-image-encryption-for-iot",totalDownloads:5,totalDimensionsCites:0,doi:"10.5772/intechopen.104431",abstract:"IoT networks serve as a way for various devices interconnected over the internet to exchange data with each other and with other services. Most smartphones, laptops, and other communication devices are connected to the cloud today, making data accessible to everyone. There are many applications for IoT, from smart IoT applications to industrial products. Encryption is one of the best ways to make IoT networks secure since so much data is being transferred. A lightweight block cipher is one of the most sophisticated means for overcoming the security problems inherent to IoT networks. Because of the limited resources available to nodes, classical cryptography methods are costly and inefficient. In this paper, we have compared the systems, we have found that these modifications were made to the original AES algorithm, while the original algorithm security remains robust, the modified AES algorithm remains lightweight and faster, providing more satisfaction for embedding in IoT devices and sensors that consume little power. Furthermore, this algorithm enhanced the AES-ECC hybrid encryption system, which has good flexibility and versatility, and optimized the design of the ECC function according to the characteristics of wireless sensor networks. Using Salsa20/12 stream cipher, the texture images can be encrypted using bit masking and permutation procedures and as part of a new scheme for encrypting 3D objects, which complements the existing methods for 3D object encryption. With PLIE implemented in Python, the encryption time was approximately 50% faster than that of AES using the throughput increase, faster encryption time, and minimal complexity.",book:{id:"11190",title:"Lightweight Cryptographic Techniques and Cybersecurity Approaches",coverURL:"https://cdn.intechopen.com/books/images_new/11190.jpg"},signatures:"Haneen Dweik and Mohammad Abutaha"},{id:"82098",title:"Perspective chapter: Internet of Things in Healthcare - New Trends, Challenges and Hurdles",slug:"perspective-chapter-internet-of-things-in-healthcare-new-trends-challenges-and-hurdles",totalDownloads:5,totalDimensionsCites:0,doi:"10.5772/intechopen.104946",abstract:"Applied to health field, Internet of Things (IoT) systems provides continuous and ubiquitous monitoring and assistance, allowing the creation of valuable tools for diagnosis, health empowerment, and personalized treatment, among others. Advances in these systems follow different approaches, such as the integration of new protocols and standards, combination with artificial intelligence algorithms, application of big data processing methodologies, among others. These new systems and applications also should face different challenges when applying this kind of technology into health areas, such as the management of personal data sensed, integration with electronic health records, make sensing devices comfortable to wear, and achieve an accurate acquisition of the sensed data. 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He was elected a Yangtze River Scholars Distinguished Professor in 2013, a member of the International Statistical Institute (ISI) in 2016, a member of the board of the International Chinese Statistical Association (ICSA) in 2018, and a fellow of the Institute of Mathematical Statistics (IMS) in 2021. He received the ICSA Outstanding Service Award in 2018 and the National Science Foundation for Distinguished Young Scholars of China in 2012. He serves as a member of the editorial board of Statistics and Its Interface and Journal of Systems Science and Complexity. He is also a field editor for Communications in Mathematics and Statistics. His research interests include biostatistics, empirical likelihood, missing data analysis, variable selection, high-dimensional data analysis, Bayesian statistics, and data science. He has published more than 190 research papers and authored five books.",institutionString:"Yunnan University",institution:{name:"Yunnan University",country:{name:"China"}}},{id:"1177",title:"Prof.",name:"António",middleName:"J. R.",surname:"José Ribeiro Neves",slug:"antonio-jose-ribeiro-neves",fullName:"António José Ribeiro Neves",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1177/images/system/1177.jpg",biography:"Prof. António J. R. Neves received a Ph.D. in Electrical Engineering from the University of Aveiro, Portugal, in 2007. Since 2002, he has been a researcher at the Institute of Electronics and Informatics Engineering of Aveiro. Since 2007, he has been an assistant professor in the Department of Electronics, Telecommunications, and Informatics, University of Aveiro. He is the director of the undergraduate course on Electrical and Computers Engineering and the vice-director of the master’s degree in Electronics and Telecommunications Engineering. He is an IEEE Senior Member and a member of several other research organizations worldwide. His main research interests are computer vision, intelligent systems, robotics, and image and video processing. He has participated in or coordinated several research projects and received more than thirty-five awards. He has 161 publications to his credit, including books, book chapters, journal articles, and conference papers. He has vast experience as a reviewer of several journals and conferences. As a professor, Dr. Neves has supervised several Ph.D. and master’s students and was involved in more than twenty-five different courses.",institutionString:null,institution:{name:"University of Aveiro",country:{name:"Portugal"}}},{id:"11317",title:"Dr.",name:"Francisco",middleName:null,surname:"Javier Gallegos-Funes",slug:"francisco-javier-gallegos-funes",fullName:"Francisco Javier Gallegos-Funes",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/11317/images/system/11317.png",biography:"Francisco J. Gallegos-Funes received his Ph.D. in Communications and Electronics from the Instituto Politécnico Nacional de México (National Polytechnic Institute of Mexico) in 2003. He is currently an associate professor in the Escuela Superior de Ingeniería Mecánica y Eléctrica (Mechanical and Electrical Engineering Higher School) at the same institute. His areas of scientific interest are signal and image processing, filtering, steganography, segmentation, pattern recognition, biomedical signal processing, sensors, and real-time applications.",institutionString:"Instituto Politécnico Nacional",institution:{name:"Instituto Politécnico Nacional",country:{name:"Mexico"}}},{id:"428449",title:"Dr.",name:"Ronaldo",middleName:null,surname:"Ferreira",slug:"ronaldo-ferreira",fullName:"Ronaldo Ferreira",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/428449/images/21449_n.png",biography:null,institutionString:null,institution:{name:"University of Aveiro",country:{name:"Portugal"}}},{id:"165328",title:"Dr.",name:"Vahid",middleName:null,surname:"Asadpour",slug:"vahid-asadpour",fullName:"Vahid Asadpour",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/165328/images/system/165328.jpg",biography:"Vahid Asadpour, MS, Ph.D., is currently with the Department of Research and Evaluation, Kaiser Permanente Southern California. He has both an MS and Ph.D. in Biomedical Engineering. He was previously a research scientist at the University of California Los Angeles (UCLA) and visiting professor and researcher at the University of North Dakota. He is currently working in artificial intelligence and its applications in medical signal processing. In addition, he is using digital signal processing in medical imaging and speech processing. Dr. Asadpour has developed brain-computer interfacing algorithms and has published books, book chapters, and several journal and conference papers in this field and other areas of intelligent signal processing. He has also designed medical devices, including a laser Doppler monitoring system.",institutionString:"Kaiser Permanente Southern California",institution:null},{id:"169608",title:"Prof.",name:"Marian",middleName:null,surname:"Găiceanu",slug:"marian-gaiceanu",fullName:"Marian Găiceanu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/169608/images/system/169608.png",biography:"Prof. Dr. Marian Gaiceanu graduated from the Naval and Electrical Engineering Faculty, Dunarea de Jos University of Galati, Romania, in 1997. He received a Ph.D. (Magna Cum Laude) in Electrical Engineering in 2002. Since 2017, Dr. Gaiceanu has been a Ph.D. supervisor for students in Electrical Engineering. He has been employed at Dunarea de Jos University of Galati since 1996, where he is currently a professor. Dr. Gaiceanu is a member of the National Council for Attesting Titles, Diplomas and Certificates, an expert of the Executive Agency for Higher Education, Research Funding, and a member of the Senate of the Dunarea de Jos University of Galati. He has been the head of the Integrated Energy Conversion Systems and Advanced Control of Complex Processes Research Center, Romania, since 2016. He has conducted several projects in power converter systems for electrical drives, power quality, PEM and SOFC fuel cell power converters for utilities, electric vehicles, and marine applications with the Department of Regulation and Control, SIEI S.pA. (2002–2004) and the Polytechnic University of Turin, Italy (2002–2004, 2006–2007). He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and cofounder-member of the IEEE Power Electronics Romanian Chapter. He is a guest editor at Energies and an academic book editor for IntechOpen. He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. Dr. Gaiceanu has been General Chairman of the IEEE International Symposium on Electrical and Electronics Engineering in the last six editions.",institutionString:'"Dunarea de Jos" University of Galati',institution:{name:'"Dunarea de Jos" University of Galati',country:{name:"Romania"}}},{id:"4519",title:"Prof.",name:"Jaydip",middleName:null,surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/4519/images/system/4519.jpeg",biography:"Jaydip Sen is associated with Praxis Business School, Kolkata, India, as a professor in the Department of Data Science. His research areas include security and privacy issues in computing and communication, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. He has been listed among the top 2% of scientists in the world for the last three consecutive years, 2019 to 2021 as per studies conducted by the Stanford University, USA.",institutionString:"Praxis Business School",institution:null},{id:"320071",title:"Dr.",name:"Sidra",middleName:null,surname:"Mehtab",slug:"sidra-mehtab",fullName:"Sidra Mehtab",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002v6KHoQAM/Profile_Picture_1584512086360",biography:"Sidra Mehtab has completed her BS with honors in Physics from Calcutta University, India in 2018. She has done MS in Data Science and Analytics from Maulana Abul Kalam Azad University of Technology (MAKAUT), Kolkata, India in 2020. Her research areas include Econometrics, Time Series Analysis, Machine Learning, Deep Learning, Artificial Intelligence, and Computer and Network Security with a particular focus on Cyber Security Analytics. Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:{name:"Association for Computing Machinery",country:{name:"United States of America"}}},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:'"Politechnica" University Timişoara',institution:null},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"310576",title:"Prof.",name:"Erick Giovani",middleName:null,surname:"Sperandio Nascimento",slug:"erick-giovani-sperandio-nascimento",fullName:"Erick Giovani Sperandio Nascimento",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0033Y00002pDKxDQAW/ProfilePicture%202022-06-20%2019%3A57%3A24.788",biography:"Prof. Erick Sperandio is the Lead Researcher and professor of Artificial Intelligence (AI) at SENAI CIMATEC, Bahia, Brazil, also working with Computational Modeling (CM) and HPC. He holds a PhD in Environmental Engineering in the area of Atmospheric Computational Modeling, a Master in Informatics in the field of Computational Intelligence and Graduated in Computer Science from UFES. He currently coordinates, leads and participates in R&D projects in the areas of AI, computational modeling and supercomputing applied to different areas such as Oil and Gas, Health, Advanced Manufacturing, Renewable Energies and Atmospheric Sciences, advising undergraduate, master's and doctoral students. He is the Lead Researcher at SENAI CIMATEC's Reference Center on Artificial Intelligence. In addition, he is a Certified Instructor and University Ambassador of the NVIDIA Deep Learning Institute (DLI) in the areas of Deep Learning, Computer Vision, Natural Language Processing and Recommender Systems, and Principal Investigator of the NVIDIA/CIMATEC AI Joint Lab, the first in Latin America within the NVIDIA AI Technology Center (NVAITC) worldwide program. He also works as a researcher at the Supercomputing Center for Industrial Innovation (CS2i) and at the SENAI Institute of Innovation for Automation (ISI Automação), both from SENAI CIMATEC. He is a member and vice-coordinator of the Basic Board of Scientific-Technological Advice and Evaluation, in the area of Innovation, of the Foundation for Research Support of the State of Bahia (FAPESB). He serves as Technology Transfer Coordinator and one of the Principal Investigators at the National Applied Research Center in Artificial Intelligence (CPA-IA) of SENAI CIMATEC, focusing on Industry, being one of the six CPA-IA in Brazil approved by MCTI / FAPESP / CGI.br. He also participates as one of the representatives of Brazil in the BRICS Innovation Collaboration Working Group on HPC, ICT and AI. He is the coordinator of the Work Group of the Axis 5 - Workforce and Training - of the Brazilian Strategy for Artificial Intelligence (EBIA), and member of the MCTI/EMBRAPII AI Innovation Network Training Committee. He is the coordinator, by SENAI CIMATEC, of the Artificial Intelligence Reference Network of the State of Bahia (REDE BAH.IA). 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