Initialization of the algorithms’ parameters.
\r\n\tNot all mixtures of particles and liquids can be considered slurries. A slurry has its character quite different from the carrying liquid (sometimes referred to as the vehicle). A Newtonian liquid has its shear stress directly proportional to its rate of deformation, but this is seldom the case for a slurry. In general, slurries are referred to as non-Newtonian liquids and ways of dealing with them are important threads in this text.
\r\n\r\n\tPipe blockages and pipe wear cause high costs to industry, in both maintenance and loss of production. This waste, and environmental damage which comes with it, can be shown to be reduced by careful application of slurry technology. This book will welcome recent research efforts to understand slurries related to the above-mentioned topics.
",isbn:"978-1-80356-669-6",printIsbn:"978-1-80356-668-9",pdfIsbn:"978-1-80356-670-2",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,isSalesforceBook:!1,isNomenclature:!1,hash:"a3de73ad02868797334aa3024ec3f018",bookSignature:"Dr. Trevor Jones",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11907.jpg",keywords:"Slurry Rheology, Non-Newtonian Flows, Wastewater Treatment, Blood Rheology, Slurry Measurement, Slurry Tomography, Pipeline Pigs, Pipeline Cleaning, Wear, Swirl Induction, Electrical Resistance Tomography, Electrical Capacitance Tomography",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"March 22nd 2022",dateEndSecondStepPublish:"May 25th 2022",dateEndThirdStepPublish:"July 24th 2022",dateEndFourthStepPublish:"October 12th 2022",dateEndFifthStepPublish:"December 11th 2022",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"2 months",secondStepPassed:!0,areRegistrationsClosed:!0,currentStepOfPublishingProcess:4,editedByType:null,kuFlag:!1,biosketch:"Dr. Jones is a world-leading expert in naturally-occurring particle products - slurries, sludges, coal, ore, and gravel. 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Animal reproduction aims to renew generations for a given production purpose such as meat, milk, or wool according to species. In order to achieve this goal researchers look for the best control of reproduction in parents to provide a maximum number of new-born of the required quality [1].
Nowadays, many reproductive biotechnologies have been developed for the effective control of reproduction in terrestrial and aquatic animals showing great differences in reproduction types. The application of biotechnology offers many advantages to animal food production through enhancement and control of reproductive processes in terrestrial and aquatic animals.
Reproduction success is a very important target for all animal species. Animal species take different strategies to achieve this target [2]. The objective of a reproductive strategy is to maximize reproductively active offspring depending on available energy and parental life expectancy [3].
There are two forms of reproduction known as asexual and sexual. There are several ways of reproducing asexually such as fission, budding, fragmentation and parthenogenesis. Asexual reproduction occurs in prokaryotic microorganisms (bacteria and archaea) and many eukaryotic, single-celled, and multi-celled organisms.
Additionally, some animal species (including sea stars and sea anemones, as well as some insects, reptiles, and fish) are capable of asexual reproduction. The most common forms of asexual reproduction for stationary aquatic animals include budding and fragmentation where part of a parent individual can separate and grow into a new organism.
On the other hand, sexual reproduction typically depends on the sexual interaction of two specialized organisms, known as gametes, which contain a half number (n) of chromosomes of normal cells and are created via meiosis. Typically, a male fertilizes a female of the same species to create a zygote (2n). In this way, it is possible to produce offsprings whose genetic characteristics are derived from those of the two parental organisms.
After fertilization, a series of developmental stages occur in which primary germ layers are established and organized to form an embryo. During this process, animal tissues begin to organize into organs to determine their future morphology and physiology.
It is known that all terrestrial animals perform internal fertilization, whereas aquatic animals perform various reproductive systems including internal fertilization with or without mating. On the other hand, many aquatic animals perform mainly external fertilization in different types such as viviparous, oviparous, and parthenogenesis [4].
Terrestrial animals mostly perform internal fertilization and there are two ways of producing offspring via this way which are:
The first one is fertilizing of the eggs inside of the female’s body and the embryo receives nourishment from the egg yolk. When the offsprings are fully developed they are hatched.
The second one is fertilizing of the eggs inside of the female and the embryo receives nourishment from the mother’s blood through a placenta. The offspring develops inside of the female body and is born alive.
By the way of internal fertilization, the embryo is isolated within the female and is provided protection against the predators, which also increases the likelihood of fertilization of the egg by a specific male. Despite fewer offspring are produced via this fertilization type, but their survival rates are higher than that of external fertilization.
Aquatic animals mostly perform external fertilization. In general, this type of fertilization occurs in aquatic environments where both eggs and sperm are released into the water. The role of water is to protect the eggs from drying out during embryonic development. The gametes are released at the same time to the same location and provide increasing in the likelihood of fertilization of the eggs eventually. The embryo receives nourishment from the egg yolk.
Additionally, there are some strategies used by fish to ensure their offspring survive in aquatic animals. The reproductive strategies of aquatic animals are often reflected in the anatomical differences between the sexes. In this framework, aquatic animals, mainly teleost fishes, have developed a large variety of reproductive strategies, varying from mass spawning to parental care, from strict gonochorism to hermaphrodism, and from oviparity to viviparity.
Most of the fish species are gonochoric, that is their sexes are separate during their lifetime. However, many fish species exhibit sex change that is called as hermaphrodism, which can be protandrous if the fish sex changes from male to female. Other hermaphrodite species can be protogynous hermaphrodite and their sex change from female into a male. Interestingly, simultaneous hermaphrodites also exist in aquatic animals, which behave almost simultaneously as males or females. In this way, individuals can change within minutes from displaying male sexual behavior, with sperm release, to female sexual behavior, with egg-laying [5].
In oviparous fish, eggs are fertilized externally, after spawning. On the other hand, in viviparous fish, such as the guppy (
Biotechnology can be defined as a technique using living organisms to modify or improve products. Biotechnology has a great impact on species improvement, reproductive rate, and animal production. Reproductive biotechnology is modern technological technique using biological systems and organisms to develop and increase the quality of the products. The most common reproductive applications integrated with biotechnology are artificial insemination, short and long-term preservation of sperm, sperm sexing, synchronization, superovulation, embryo transfer, and
The application of biotechnology offers numerous advantages to livestock production through control of the reproductive process in animals. These biotechnologies can be summarized as artificial insemination, estrus synchronization, embryo transfer, sperm cryopreservation, transgenesis, and
Artificial insemination is one of the earliest reproductive biotechnologies and permits using of superior males for breeding purposes. It involves sperm collection from superior males, dilution of sperm, freezing of sperm, and transferring of frozen–thawed sperm to the female reproductive tract [7].
Estrus synchronization is a grouping of females for parturition at the same time. It is used at commercial dairy farms for uniform milk production throughout the year. It is closely linked with artificial insemination and is also the first step of embryo transfer. Using estrus synchronization is a good strategy to overcome breeding problems, especially during the summer months [7].
Embryo transfer is a process by which embryos are collected from a donor female and then transferred into a recipient female where the embryos complete their development. It is the most commonly used biotechnology after artificial insemination and estrus synchronization. Embryo transfer is profitable for producers of pure-bred animals and genetically superior females that produce more offspring than natural reproduction. This technique is used in several species of domestic animals including cows, horses, goats, and sheep [7].
Research on sperm cryopreservation can be traced back to the discovery of the protective peculiarity of glycerol for freezing of avian sperm by Polge et al. [8]. Since then, cryopreserved sperm of livestock has grown into a near-billion dollar global industry. Additionally, since the first successful cryopreservation of bull semen, cryopreserved sperm has been used to propagate the rare and endangered species [9].
It is clear that sperm cryopreservation contributes to the expansion of reproductive techniques, such as artificial insemination and
Successful reproduction of cultured fish broodstock is essential in terms of the sustainable aquaculture of aquatic organisms. In this concept, reproductive biotechnologies mainly include cryopreservation of male gametes, genetic control of sex, and production of transgenic fish.
Cryopreservation is the process of freezing the biological materials at the temperature of liquid nitrogen (LN2) (−196°C). In this way, it is possible to storing the biological materials as unchanged for centuries with the capability of recovering the cell functionality following the thawing process [12]. Today, sperm management techniques have been established for freshwater and marine fish species [13, 14, 15].
Cryopreservation of male gametes is an important biotechnological tool for aquatic species and has great concern for aquaculture. Following successful cryopreservation of avian spermatozoa using glycerol as cryoprotectant by Polge et al. [8], cryopreservation of male gametes became possible in aquatic animals [9]. First time, Blaxter [16] applied a similar approach for fish sperm and reported achieving approximately 80% cellular motility following thawing of Atlantic herring sperm cells. Since then, cryopreservation of fish sperm has been studied and succeeded in more than 200 species [17]. In addition, it is possible to reconstruct the original strain, population, or variety following required environmental restoration via this biotechnology [9].
The genetic control of fish sex could be useful where one sex displays advantageous characteristics such as larger adult size, production of high-value caviar, faster growth rate, or higher age at first sexual maturation. In this concept, monosex populations of the most advantageous sex may be produced through genetic control (crossing, gynogenesis, androgenesis, hybridization) or steroid treatment of broodstock (hormonal treatment) [18].
Genetic control of sex is possible via crossing, gynogenesis, androgenesis, and hybridization. In this framework, it is possible to control sex by the crossing of sex-reversed adult broodstock (administering androgens to produce “neo” males and estrogens to produce “neo” females) with normal males or females to produce single-sex progeny. Another sex control method is gynogenesis which is the fertilization of oocytes with inactivated sperm (irradiated) with normal sperm, to eliminate the female chromosomes and produce all-female progeny. Also, it is possible via androgenesis that is fertilization of inactivated oocytes (irradiated) with normal sperm, to eliminate the female chromosomes and produce all-male progeny. Additionally, another way of genetic sex control is the hybridization of two different species from the same genera producing single-sex progeny [18].
The domestic fish production through transgenic techniques offers many potential economic advantages for commercial aquaculture production. The traditional method of producing transgenic fish is still microinjection. However, some success has also been shown using particle bombardment [18].
Reproduction is the backbone of animal production and productivity is the key element for development. Reproductive inefficiency is one of the most important reasons of economic losses in animal industries. Despite the remarkable advancement in the field of reproductive physiology, low conception rate, and the high embryonic mortality rate remains a major problem in terrestrial and aquatic animals as well.
Solving an optimization problem consists in exploring a search space in order to maximize (or minimize) a given objective function. The complexities (in size or structure) of the search space and the function to be optimized lead to the use of radically different resolution methods. However, the so-called global optimization methods are generally the best suited ones considering their main advantage: that of identifying the promised regions and converging towards a global optimum.
The zero-order optimization Genetic Algorithm (GA), initially laid down by Holland [1], remain the most recognized and practiced form of Evolutionary Algorithms (EA) which are global stochastic optimization techniques that mimic Darwin’s principles of natural selection and genetic dynamics. In fact, known advantages of the GA include its ability to combine both exploration and exploitation in an optimal way [1] in addition to its ability to be used in the case of discontinuous objective functions, within disjoined and/or non-convex design spaces, and together with discrete, continuous, or even mixed design variables. Besides, as a population-based method, GA, if initially well-tuned, minimizes the risk to converge to a local optimum thanks to the simultaneous processing of the whole candidate solutions instead of, for instance, gradient-based methods, giving thus the designer a multitude of options.
Nevertheless, like any optimization technique, GA has also its drawbacks starting with the numerous parameters sensitivity analysis to do to maximize efficiency and have a good initialization of the algorithm. In addition to the most notable drawback which is generally the great number of required iterations, and they slow convergence, especially in the neighborhood of the global optimum. Indeed, although GAs can rapidly locate the region in which the global optimum exists, they take a relatively long time to locate the exact local optimum in the region of convergence. Each generation of the algorithm consists of many objective function evaluations resulting in a lot of computational time in addition to being very expensive.
To overcome this main limitation and lessen function evaluation time, different alternatives have been proposed. But particularly the trend of hybridization has been observed in many works carried out on metaheuristics over the past 20 years, where it consists of incorporating a faster Local Search (LS) (or individual learning) optimization algorithm into a GA in order to improve the performance of the global resulting method, often known as Memetic Algorithm (MA). This latter was first introduced by Moscato [2] and is representing one of the recent growing areas of research in evolutionary computation [3] by offering the important challenge of the tradeoff between global searching and local searching in terms of time and computational effort. In fact, this integration aims to keep advantages of both optimization methods while offsetting their both disadvantages [4] As LS algorithms are actually capable to find the local optimum with high accuracy and fast convergence but suffer from the problem of foothills. Hence through their integration with the population-based method, the time needed to reach the global optimum can be further reduced since the local knowledge is used to accelerate finding the most promising search region in addition to locating the global optimum starting within its attraction basin.
These hybrid algorithms have also been used under the name of hybrid evolutionary algorithms, Baldwinian evolutionary algorithms, Lamarckian evolutionary algorithms, cultural algorithms, or genetic LS. They also have been successfully applied to hundreds of real-world problems in a wide variety of domains ranging from aircraft [5], aerospace [6], pattern recognition [7], control systems [8], vehicle routing [9], pharmaceutical industry [10] etc.
An example of a hybrid GA applied to the mechanical structures’ optimization is presented in this chapter. This test case reflects the relevance of this hybridization in the mathematical resolution of optimization problems related to the aerospace field.
The organization of the chapter is as follows: the second section is dedicated to the description of the different hybridization design including the combination between GAs and LS methods. General mechanisms of GAs are remained in the third section. Hybrid GAs are discussed in the fourth section then the test case with the problematic presentation and the obtained results is given in the fifth section. Finally, conclusions are given in the last section.
As mentioned before, in an optimization problem solving approach, it can be extremely beneficial to combine two solving techniques, knowing that it is possible to hybridize all exact and metaheuristic techniques. Hence, the hybridization can take place in one or more components of a research method. It can also consist in assembling several hybridization methods to form a single hybrid method. Two strategies can be used depending on the optimization technique which drives the hybrid method:
Strategy 1: we can approach the global optimum by a stochastic technique and then refine the result by successively applying a local one. In this case, the result will be ameliorated but unfortunately time consuming. An optimal way to use hybridization in this case may be by applying a global optimization method and find the right time to switch to a local one.
Strategy 2: we can try to find a local minimum and keep it as a winning solution if it is the best of all the local (global) minimums. For instance, in the method of multiple initializations or (multi Start), a local optimization technique is used several times at different stress points; the solution of the optimization problem would be then the best obtained result.
According to the author in [11], a taxonomy for hybrid meta-heuristics can be proposed by classifying them into three categories depending on their architecture (see Figure 1):
Hybridization classification.
Sequential hybridization: it is the most popular type; it performs different research methods sequentially so that the result of the first one serves as an initial solution for the next one.
Synchronous parallel hybridization: this hybridization is carried out by incorporating a particular research method in an operator. It is more complex to implement than the previous one. The aim is to combine a LS with a global search for the purpose of improving convergence.
Asynchronous parallel hybridization: the hybrid methods belonging to this class are characterized by an architecture such that two algorithms A and B are involved simultaneously, and each one adjusts the other. The Algorithms A and B share and exchange information throughout the research process.
A global view of the different possible hybridization schemes is shown in Figure 2 where we can see hybridization between stochastic (particularly metaheuristics) and analytical optimization methods. Indeed, the common point between all these hybridizations is that they try to merge the strengths and eliminate the weaknesses of the different concepts. Therefore, the efficiency of the search solution space can still be improved, and new opportunities emerged which may lead to even more powerful and flexible research methods.
Possible hybridization schemes.
GAs use a vocabulary inspired from natural genetics. However, the natural processes to which they refer is more complex [12]. They are iterative optimization procedures that repeatedly apply GA operators (such as selection, crossover, and mutation) to a group of solutions until some criterion of convergence has been satisfied. Note that the essential element of the genetic vocabulary is the “individual” that belongs to a set of individuals called “population”. The individual is made up of a “chromosome” which is itself made up of “genes” which contain the inheritance characteristics of the individual. The principles of “selection”, “crossover” and “mutation” are the main genetic operators that are inspired by the same natural processes. First, the selection operator includes generally two variants; the parental selection devoted for reproduction and the replacement selection devoted to keeping the population size constant by individuals who will survive in the next generation. A selection favors the best individuals but has also to give a chance to the less good to avoid the problems of premature convergence. Note that the “fitness” or “evaluation” function characterizing how well adapted the solution is to its environment, is closely related to the selection process. Then, the crossover operator involves combining the information from two parents to create one or two new individuals (or “offspring”) making it possible to diversify the population and explore more the research space. At last, the mutation operator causes a small perturbation on an individual’s chromosome thus allowing to guarantee gene diversity so that the algorithm does not get stuck in local minima. This process continues, throughout the generations, until the stop criteria is reached. The latter can be in various forms such as for example several global iterations defined in advance or the difference between the average population’s fitness and the best one.
It is also important to underline that during the implementation of the algorithm it is necessary to take into account the encoding of the different parameters. In fact, one of the characteristics of GAs is their need to a genetic representation of the desired problem using an encoding. Therefore, the algorithm can evaluate the fitness of every individual and computes the problem’s objectives and constraints based only on the encoding without any further knowledge of real parameters.
Figure 3 shows the optimization flowchart offered by GA whereas Reference [13] provides further discussion on the theoretical properties of GAs and on standard genetic operators.
Flowchart of the optimization procedure based on a genetic algorithm.
The most natural hybridization in the literature is the use of a single solution meta-heuristic algorithm embedded in a population-based meta-heuristic algorithm like the unmissable GA in order to improve the qualities of the solutions. In fact, whereas population-based meta-heuristics tend to diversify the search space by exploring it different parts, LS meta-heuristics tend to intensify the search by exploiting only one part of the space.
LS methods are based on a neighborhood relation and on a procedure exploiting this neighborhood. They consist in moving from one solution to another closer in the space of the candidate solutions, until a solution considered as optimal is found, or the allowed time is exceeded. We can therefore summarize the main idea of a LS as follows:
Start from an initial solution,
Improve that solution,
Repeat the process several times.
Hence, through the hybridization, individuals attempt to identify promising areas of the solution space which are then explored in more detail by LS methods. The best known among the latters are the simulated annealing, the tabu search or simply descent methods (iterated local searches).
Concerning the hybridization adopting the global GA, as its decision-making mechanics are based on random principles, this detailed research can be difficult to carry out. Heuristics therefore serve to fill this weakness. In a general way, at all generations, an individual (or some individuals) are randomly selected among the best in the population. Then, a set of solutions defining its (their) neighborhood is constructed. Afterwards, each of these neighbors is evaluated in order to check whether there is an improvement in the evaluation function. GA then manipulates solutions that have already been improved locally. This has the effect of allowing even more advantageous solutions to be generated more quickly. However, as there are several ways to hybridize GAs while maintaining a fairly modular program structure, a sequential approach could be advantageous in such a way that it is enough to let the GA run to a substantial level of convergence, then let the local optimization procedure follow up the process, for example by taking the
Note that usually the individuals that undergo LS are chosen uniformly at random, but it would be more efficient to use a tuning technique which consists of a primary conducted experiment aiming to find the optimal part of the population that should perform LS. This part is commonly referred to as the LS probability mentioned above that is used to run the actual experiment and remains fixed during the algorithm execution. In the literature, several techniques aim to reduce unnecessary local optimization and therefore additional calculation time, such as distribution-based techniques [15], fitness-based techniques [15] and LS potential [16] that have been proposed to select the optimal individuals among the given population that should do a LS. In the following, some main LS methods are remained.
Simulated annealing is an optimization technique inspired by the simulation methods of Metropolis (1950s) in statistical mechanics. It is distinguished by the introduction of a temperature parameter which is adjusted during research [17]. Moreover, in optimization, this method considers a neighborhood exploitation procedure which makes it possible to go towards a neighboring solution of less good quality with a non-zero probability, thus allowing to escape the local optima.
At the beginning, a “temperature” parameter T is determined and decreases throughout the algorithm to tend towards 0. The probability of accepting deteriorated solutions depends on the value of this parameter (the more the temperature T decreases, the more this probability decreases). The interest of simulated annealing lies in the fact that there is a proof of its asymptotic convergence. Thus, when certain conditions are verified (decrease diagram of T), we are guaranteed to obtain the optimal solution. However, the parameterization recommended by theory is not very realistic and it takes a long time to get to parameterize these methods. Note that this method may also require a stop criterion, if the “optimal” setting has not been found. Hybridization between GA and SA algorithms has been used in several domains [18, 19, 20].
Tabu search was introduced as a new strategy to escape local optima using a notion of memory [21]. Exploitation of the neighborhood makes it possible to move from the current solution to its best neighbor (this one not necessarily having a better quality than the current solution). To avoid cycling between a local optimum and its best neighbor, the method prohibits moving to a recently visited solution. To do this, a tabu list containing the attributes of the last visited solutions is kept up to date. Each new solution considered removes the oldest visited solution from this list. Thus, the search for the following current solution is done in the neighborhood of the current solution without considering the solutions belonging to the tabu list. However, the size of this list is a method parameter that is difficult to adjust. In addition, this strategy requires the definition of a stopping criterion. We find the hybridization between GA and TS in many applications such as image processing [22], computational grids [23] and flow shop scheduling problem [24].
The descent methods are quick and simple to implement but generally do not lead to the best optima because they stop as soon as a local optimum is found [25]. In order not to get stuck on this local optimum, there are various strategies which allow the search to continue after having found an optimum. One strategy to overcome the abrupt stopping of the search for a local optimum is to iterate the descent method. The following steps are carried out from the found optimum:
Apply a perturbation on the current solution,
Apply a descent method on that solution.
Chose via an acceptance criterion if the new optimum becomes the current solution and go back to the first step until the stop criterion is reached. Common stop criteria are the execution time, the number of iterations and the number of total evaluations.
The disturbance can consist in restarting a solution taken randomly in the search space or in choosing a solution in a neighborhood far from the optimum or even in choosing a neighbor of the same quality as the optimum.
Heuristic Iterative Local Search (ILS) [26] is based on a simple idea: instead of repeatedly applying a LS procedure from randomly generated solutions, ILS generates the starting solution for the next iteration by applying a perturbation on the local optimum found at the current iteration. This is done in the hope that the disturbance mechanism provides a solution located in the attraction basin of a better local optimum. Therefore, the disruption mechanism is a key part of ILS. In addition, an acceptance criterion defines the conditions that the new local optimum must meet in order to replace the current local optimum (Figure 4). Thus, the acceptance criterion, combined with the disruption mechanism, helps to control the trade-off between intensification and diversification. However, many acceptance criteria which reconcile the two objectives can be applied [12]. Hybridization between GA and ILS is one of the simplest and common hybridizations that can be found in several works [27, 28, 29].
From a local minimum s, a disturbance of the latter generates a minimum s’ from which a LS is launched to arrive at a third local minimum s” potentially better than s.
The Variable Neighborhood Search (VNS) is a meta-heuristic algorithm [30], based on the principle of systematic neighborhood change during LS. Indeed, at the initialization step, a set of neighborhood structures must be defined. These neighborhoods can be chosen arbitrarily, but often a sequence ordered in size growing neighborhoods is used. The VNS procedure consists of three stages: (1) the disturbance (shaking), (2) the LS and (3) the displacement. Recently, a variety of problems have involved hybridization between GA and VNS [31, 32, 33].
We consider here the following optimization problem: search for the minimum mass of an inter-stage skirt made of composite sandwich with Carbon Fiber Reinforced Polymer (CFRP) skins and aluminum Nida core (composites are fabricated by attaching two thin but stiff skins to a lightweight but thick core) that are located between the first stage and the second stage situated on the upper part of a linear launcher (Figure 5).
Simplified model of the sandwich composite inter-stage skirt (in red) located on the upper part of the linear launcher.
The structure is subjected to pressure oscillations from upstream solid propellant engines to ensure “payload comfort”. The skirt therefore has a filtering role in order to limit the vibratory levels at the top of the launcher. To best dampen these oscillations, the structure must be mechanical sized according to a compromise between rigidity and flexibility linked to the need to hold in buckling, in addition to composite manufacturing constraints (mirror symmetry, balancing, grouping) [34]. Note that we need to optimize only one skin plus the core hence the final result is obtained by symmetry.
Mathematically speaking, we can write the optimization problem as follows:
Subject to:
To solve the above optimization problem, we have chosen the global GA. In fact, during the mechanical sizing of a composite structure, plies thicknesses are often predetermined, and plies orientations are usually restricted to a small set of angles due to manufacturing constraints and/or limited availability of experimental data. Most of the time, this gives rise mathematically to a discrete optimization problem. Hence GA is a suitable optimization method that we also decided to hybridize with a LS method to overcome the drawbacks of GA cited throughout this chapter.
First of all, an appropriate representation of the problem is recommended through the encoding of all the parameters. In fact, the initial population of the GA is composed of a set of skin plies (sandwich case) characterized by fiber orientations. Thus, an individual in the population is equivalent to a laminate (set of plies) and can simply be represented by an orientation chromosome (see Figure 6). Plies and core thicknesses of the structure are predefined based on composite design constraints [35] and are not considered herein as optimization variables. Therefore, an individual (a laminate) is represented by one chromosome regrouping one skin plies characterized by orientation angles (0°, 90°, ± 45°, ± 30°), encoded according to 5 possible values {0, 1, 2, 3, 4} called the chromosome domain where particularly add where 0° is encoded by 0, 90° is encoded by 1, ± 45° is encoded by 2, “no ply” is encoded by 3 and finally ± 30° is encoded by 4. “no ply” is encoded by 3.
The genetic representation of the design variables.
To handle constraints, concerning the composite manufacturing ones, a repair strategy is adopted during the decoding phase (Figure 7). More explanation about these constraints handling method could be seen in [36]. Whereas mechanical constraints (buckling and stiffness) are managed through the genetic selection operator.
Example of the decoding and repair strategy.
The proposed Hybrid Genetic Algorithm (HGA) herein is based on a strong and sequential cooperation between GA and a descent LS technique for the entire course of the algorithm where the LS optimization is integrated at the beginning of the GA previous to the genetic operators to intensify research only around selected promising solutions. Hence, the adopted scheme is as follows: for every new iteration, the best individual reached by the GA is selected as an initialization for the LS method. Then, a set of two neighbors is built following a well-defined structure. The latter aims to verify if there is any neighboring orientation that allows an improvement of the individual’s fitness by randomly selecting a gene related to the orientation and flipping it to either the previous or the next value in the concerned chromosome’s domain while of course respecting all manufacturing constraints via the repair cited repair strategy. For example, if the selected gene’s code is 2, the value of this gene will be replaced by 1 in the first neighbor and by 3 in the second one. However, if the randomly selected gene is the domain’s upper bound (4) or the lower one, then the two neighbors are built by flipping firstly the gene to the previous value in the domain (3) then to the lower bound (0) or conversely.
Afterwards, each neighbor is evaluated and if one’s fitness turns out to be better, then it is introduced in the population to replace the first individual and so onFigure 7 shows an example of the decoding and repair stategy where the steps decoding then reparing are explained, the randomly selected gene’s code is 2, corresponding to 90°. In order to respect the balancing composite rule, that gene should be replaced by -30° (repair) so the entire laminate respects the composite design constraints. The Figure 8 shows the adopted HGA flowchart.
Flowchart of the optimization procedure based on the hybrid genetic algorithm (HGA).
A comparative study between the classical GA and the proposed HGA is presented in the following. GA and HGA are implemented in a Python 3 environment and computed based on the same parameters (see Table 1). Note that at each iteration, the algorithms run through a database containing individuals already assessed with their respective fitness calculated through the finite element analysis program called NASTRAN [37] and look for the latter from the stacks previously evaluated. Besides, two criteria are implemented to stop the running of GA: the first stops the algorithm after a fixed number of generations have been created whereas the second stops after a given number of generations without improvement of the best individual in the population. This second criterion assures a certain quality of the best design, even if it is only relative to the previous best design. The comparison criterion is the fitness and the execution time associated with the number of iterations to achieve convergence. Concerning the HGA, the stop criteria is a prior fixed number of iterations.
Parameters | Values |
---|---|
Total number of iterations | 100 |
Number of individuals per generation | 30 |
Chromosomes’ size | 8 |
Mutation probability | 0,2 |
Mutant gene per individual | 1 |
Crossover probability | 1 |
Number of individuals chosen during the selection | 1 |
Number of iterations for the LS | 5 |
Number of neighbors per individual | 2 |
Initialization of the algorithms’ parameters.
Table 2 summarizes the optimization results. After 100 iterations, the best reached laminate is composed of 6 plies per skin against 8 initially and respects all the design constraints of composite structures thanks to the adopted decoding and repair strategy. Besides both stiffness and buckling constraints are satisfied with margins of +39.2% and + 5.9% for GA and HGA, respectively. Furthermore, the total mass is decreased by 8.4% compared to reference. This shows that generally all genetic processes perform well by offering a convincing solution. In fact, the program converges always towards the optimal solution. However, HGA provides a decrease from 26 to 18 in the number of needed iterations to converge with a gain of 24 minutes on the associated elapsed time. Thereby, HGA can outperform the standard GA on this sandwich composite structure optimization problem which highlight the hybridization mechanism and its capacity in the improvement of convergence.
Laminate (°) | S < 2e8 (N/m) | B | M (Kg) | Convergence (Iterations/Time CPU) | |
---|---|---|---|---|---|
NASTRAN | [45/0/30/0/−30/0/45/90] | 1.9e8 | 2.73 | 357 | — |
GA | [30/0/−30/30/−30/90] | 1.4e8 | 2.15 | 327 | 26/70 min |
HGA | [30/0/−30/30/−30/90] | 1.4e8 | 2.15 | 327 | 18/54 min |
Results of the comparative study between GA and HGA.
In this chapter we have underlined the importance of the process of hybridization in ameliorating the global genetic algorithm behavior and especially its convergence. In fact, although genetic algorithms are effective complete search algorithms able to combine both exploration and exploitation with crossover and mutation operators, they suffer from being computationally expensive and can hence be improved using local search methods, so they can be made competitive with other algorithms when the search space is too large to explore. More generally, the combination of metaheuristics based on population as well as on local search, may offer more effective and dynamic methods for the solution of several problems.
The following important questions were asked: (1) when to apply local search optimization (2) to which individuals in the genetic algorithm should local searches be applied, and (3) what are the possible hybridizations that could improve the optimization results. Some answers to these questions have been provided particularly the reminder of the hybridization strategies and its different possible architectures in addition to the main local search methods known by their relevant coupling with the classical genetic algorithm. The latter being able to undergo different forms of hybridization thanks to its flexibility which is nevertheless one of its strongest points.
The application possibilities of these approaches are unlimited but in this chapter the test case that was presented is about an optimization algorithm combining traditional genetic operators with an iterated local search method specially designed to pursue the problem of mechanical sizing of a composite structure. The genetic algorithm was chosen as the global optimization tool because of its ability to deal with non-convex and discrete optimization problems, of which the design of laminated composites is an example. Besides, its flexible structure makes it possible to integrate the management of different mechanical and manufacturing constraints through genetic operators and the implementation of specific optimization processes such as the decoding and repair strategy. The developed hybrid algorithm was validated by comparing its results to those obtained via the classical genetic algorithm as well as a reference finite element analysis software. That test case showed hence that the developed hybrid genetic approach is able to obtain efficient results in a real-world problem related to the aerospace sector.
The author wishes to thank the French National Center for Space Studies that partially supported this work.
The authors declare no conflict of interest.
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Recently, he expanded his research interest to epidemiology and biostatistics of chronic diseases in Gabon.",institutionString:"Kent State University",institution:{name:"Kent State University",country:{name:"United States of America"}}},{id:"188773",title:"Prof.",name:"Emmanuel",middleName:null,surname:"Drouet",slug:"emmanuel-drouet",fullName:"Emmanuel Drouet",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/188773/images/system/188773.png",biography:"Emmanuel Drouet, PharmD, is a Professor of Virology at the Faculty of Pharmacy, the University Grenoble-Alpes, France. As a head scientist at the Institute of Structural Biology in Grenoble, Dr. Drouet’s research investigates persisting viruses in humans (RNA and DNA viruses) and the balance with our host immune system. He focuses on these viruses’ effects on humans (both their impact on pathology and their symbiotic relationships in humans). He has an excellent track record in the herpesvirus field, and his group is engaged in clinical research in the field of Epstein-Barr virus diseases. He is the editor of the online Encyclopedia of Environment and he coordinates the Universal Health Coverage education program for the BioHealth Computing Schools of the European Institute of Science.",institutionString:null,institution:{name:"Grenoble Alpes University",country:{name:"France"}}},{id:"131400",title:"Prof.",name:"Alfonso J.",middleName:null,surname:"Rodriguez-Morales",slug:"alfonso-j.-rodriguez-morales",fullName:"Alfonso J. Rodriguez-Morales",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/131400/images/system/131400.png",biography:"Dr. Rodriguez-Morales is an expert in tropical and emerging diseases, particularly zoonotic and vector-borne diseases (especially arboviral diseases). He is the president of the Travel Medicine Committee of the Pan-American Infectious Diseases Association (API), as well as the president of the Colombian Association of Infectious Diseases (ACIN). He is a member of the Committee on Tropical Medicine, Zoonoses, and Travel Medicine of ACIN. He is a vice-president of the Latin American Society for Travel Medicine (SLAMVI) and a Member of the Council of the International Society for Infectious Diseases (ISID). Since 2014, he has been recognized as a Senior Researcher, at the Ministry of Science of Colombia. He is a professor at the Faculty of Medicine of the Fundacion Universitaria Autonoma de las Americas, in Pereira, Risaralda, Colombia. He is an External Professor, Master in Research on Tropical Medicine and International Health, Universitat de Barcelona, Spain. He is also a professor at the Master in Clinical Epidemiology and Biostatistics, Universidad Científica del Sur, Lima, Peru. In 2021 he has been awarded the “Raul Isturiz Award” Medal of the API. Also, in 2021, he was awarded with the “Jose Felix Patiño” Asclepius Staff Medal of the Colombian Medical College, due to his scientific contributions to COVID-19 during the pandemic. He is currently the Editor in Chief of the journal Travel Medicine and Infectious Diseases. His Scopus H index is 47 (Google Scholar H index, 68).",institutionString:"Institución Universitaria Visión de las Américas, Colombia",institution:null},{id:"332819",title:"Dr.",name:"Chukwudi Michael",middleName:"Michael",surname:"Egbuche",slug:"chukwudi-michael-egbuche",fullName:"Chukwudi Michael Egbuche",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/332819/images/14624_n.jpg",biography:"I an Dr. Chukwudi Michael Egbuche. I am a Senior Lecturer in the Department of Parasitology and Entomology, Nnamdi Azikiwe University, Awka.",institutionString:null,institution:{name:"Nnamdi Azikiwe University",country:{name:"Nigeria"}}},{id:"284232",title:"Mr.",name:"Nikunj",middleName:"U",surname:"Tandel",slug:"nikunj-tandel",fullName:"Nikunj Tandel",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/284232/images/8275_n.jpg",biography:'Mr. Nikunj Tandel has completed his Master\'s degree in Biotechnology from VIT University, India in the year of 2012. He is having 8 years of research experience especially in the field of malaria epidemiology, immunology, and nanoparticle-based drug delivery system against the infectious diseases, autoimmune disorders and cancer. He has worked for the NIH funded-International Center of Excellence in Malaria Research project "Center for the study of complex malaria in India (CSCMi)" in collaboration with New York University. The preliminary objectives of the study are to understand and develop the evidence-based tools and interventions for the control and prevention of malaria in different sites of the INDIA. Alongside, with the help of next-generation genomics study, the team has studied the antimalarial drug resistance in India. Further, he has extended his research in the development of Humanized mice for the study of liver-stage malaria and identification of molecular marker(s) for the Artemisinin resistance. At present, his research focuses on understanding the role of B cells in the activation of CD8+ T cells in malaria. Received the CSIR-SRF (Senior Research Fellow) award-2018, FIMSA (Federation of Immunological Societies of Asia-Oceania) Travel Bursary award to attend the IUIS-IIS-FIMSA Immunology course-2019',institutionString:"Nirma University",institution:{name:"Nirma University",country:{name:"India"}}},{id:"334383",title:"Ph.D.",name:"Simone",middleName:"Ulrich",surname:"Ulrich Picoli",slug:"simone-ulrich-picoli",fullName:"Simone Ulrich Picoli",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/334383/images/15919_n.jpg",biography:"Graduated in Pharmacy from Universidade Luterana do Brasil (1999), Master in Agricultural and Environmental Microbiology from Federal University of Rio Grande do Sul (2002), Specialization in Clinical Microbiology from Universidade de São Paulo, USP (2007) and PhD in Sciences in Gastroenterology and Hepatology (2012). She is currently an Adjunct Professor at Feevale University in Medicine and Biomedicine courses and a permanent professor of the Academic Master\\'s Degree in Virology. She has experience in the field of Microbiology, with an emphasis on Bacteriology, working mainly on the following topics: bacteriophages, bacterial resistance, clinical microbiology and food microbiology.",institutionString:null,institution:{name:"Universidade Feevale",country:{name:"Brazil"}}},{id:"229220",title:"Dr.",name:"Amjad",middleName:"Islam",surname:"Aqib",slug:"amjad-aqib",fullName:"Amjad Aqib",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/229220/images/system/229220.png",biography:"Dr. Amjad Islam Aqib obtained a DVM and MSc (Hons) from University of Agriculture Faisalabad (UAF), Pakistan, and a PhD from the University of Veterinary and Animal Sciences Lahore, Pakistan. Dr. Aqib joined the Department of Clinical Medicine and Surgery at UAF for one year as an assistant professor where he developed a research laboratory designated for pathogenic bacteria. Since 2018, he has been Assistant Professor/Officer in-charge, Department of Medicine, Manager Research Operations and Development-ORIC, and President One Health Club at Cholistan University of Veterinary and Animal Sciences, Bahawalpur, Pakistan. He has nearly 100 publications to his credit. His research interests include epidemiological patterns and molecular analysis of antimicrobial resistance and modulation and vaccine development against animal pathogens of public health concern.",institutionString:"Cholistan University of Veterinary and Animal Sciences",institution:{name:"University of Agriculture Faisalabad",country:{name:"Pakistan"}}},{id:"333753",title:"Dr.",name:"Rais",middleName:null,surname:"Ahmed",slug:"rais-ahmed",fullName:"Rais Ahmed",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/333753/images/20168_n.jpg",biography:null,institutionString:null,institution:{name:"University of Agriculture Faisalabad",country:{name:"Pakistan"}}},{id:"62900",title:"Prof.",name:"Fethi",middleName:null,surname:"Derbel",slug:"fethi-derbel",fullName:"Fethi Derbel",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/62900/images/system/62900.jpeg",biography:"Professor Fethi Derbel was born in 1960 in Tunisia. He received his medical degree from the Sousse Faculty of Medicine at Sousse, University of Sousse, Tunisia. He completed his surgical residency in General Surgery at the University Hospital Farhat Hached of Sousse and was a member of the Unit of Liver Transplantation in the University of Rennes, France. He then worked in the Department of Surgery at the Sahloul University Hospital in Sousse. Professor Derbel is presently working at the Clinique les Oliviers, Sousse, Tunisia. His hospital activities are mostly concerned with laparoscopic, colorectal, pancreatic, hepatobiliary, and gastric surgery. He is also very interested in hernia surgery and performs ventral hernia repairs and inguinal hernia repairs. He has been a member of the GREPA and Tunisian Hernia Society (THS). During his residency, he managed patients suffering from diabetic foot, and he was very interested in this pathology. For this reason, he decided to coordinate a book project dealing with the diabetic foot. Professor Derbel has published many articles in journals and collaborates intensively with IntechOpen Access Publisher as an editor.",institutionString:"Clinique les Oliviers",institution:null},{id:"300144",title:"Dr.",name:"Meriem",middleName:null,surname:"Braiki",slug:"meriem-braiki",fullName:"Meriem Braiki",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/300144/images/system/300144.jpg",biography:"Dr. Meriem Braiki is a specialist in pediatric surgeon from Tunisia. She was born in 1985. She received her medical degree from the University of Medicine at Sousse, Tunisia. She achieved her surgical residency training periods in Pediatric Surgery departments at University Hospitals in Monastir, Tunis and France.\r\nShe is currently working at the Pediatric surgery department, Sidi Bouzid Hospital, Tunisia. Her hospital activities are mostly concerned with laparoscopic, parietal, urological and digestive surgery. She has published several articles in diffrent journals.",institutionString:"Sidi Bouzid Regional Hospital",institution:null},{id:"229481",title:"Dr.",name:"Erika M.",middleName:"Martins",surname:"de Carvalho",slug:"erika-m.-de-carvalho",fullName:"Erika M. de Carvalho",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/229481/images/6397_n.jpg",biography:null,institutionString:null,institution:{name:"Oswaldo Cruz Foundation",country:{name:"Brazil"}}},{id:"186537",title:"Prof.",name:"Tonay",middleName:null,surname:"Inceboz",slug:"tonay-inceboz",fullName:"Tonay Inceboz",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/186537/images/system/186537.jfif",biography:"I was graduated from Ege University of Medical Faculty (Turkey) in 1988 and completed his Med. PhD degree in Medical Parasitology at the same university. I became an Associate Professor in 2008 and Professor in 2014. I am currently working as a Professor at the Department of Medical Parasitology at Dokuz Eylul University, Izmir, Turkey.\n\nI have given many lectures, presentations in different academic meetings. I have more than 60 articles in peer-reviewed journals, 18 book chapters, 1 book editorship.\n\nMy research interests are Echinococcus granulosus, Echinococcus multilocularis (diagnosis, life cycle, in vitro and in vivo cultivation), and Trichomonas vaginalis (diagnosis, PCR, and in vitro cultivation).",institutionString:"Dokuz Eylül University",institution:{name:"Dokuz Eylül University",country:{name:"Turkey"}}},{id:"71812",title:"Prof.",name:"Hanem Fathy",middleName:"Fathy",surname:"Khater",slug:"hanem-fathy-khater",fullName:"Hanem Fathy Khater",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/71812/images/1167_n.jpg",biography:"Prof. Khater is a Professor of Parasitology at Benha University, Egypt. She studied for her doctoral degree, at the Department of Entomology, College of Agriculture, Food and Natural Resources, University of Missouri, Columbia, USA. She has completed her Ph.D. degrees in Parasitology in Egypt, from where she got the award for “the best scientific Ph.D. dissertation”. She worked at the School of Biological Sciences, Bristol, England, the UK in controlling insects of medical and veterinary importance as a grant from Newton Mosharafa, the British Council. Her research is focused on searching of pesticides against mosquitoes, house flies, lice, green bottle fly, camel nasal botfly, soft and hard ticks, mites, and the diamondback moth as well as control of several parasites using safe and natural materials to avoid drug resistances and environmental contamination.",institutionString:null,institution:{name:"Banha University",country:{name:"Egypt"}}},{id:"99780",title:"Prof.",name:"Omolade",middleName:"Olayinka",surname:"Okwa",slug:"omolade-okwa",fullName:"Omolade Okwa",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/99780/images/system/99780.jpg",biography:"Omolade Olayinka Okwa is presently a Professor of Parasitology at Lagos State University, Nigeria. She has a PhD in Parasitology (1997), an MSc in Cellular Parasitology (1992), and a BSc (Hons) Zoology (1990) all from the University of Ibadan, Nigeria. She teaches parasitology at the undergraduate and postgraduate levels. She was a recipient of a Commonwealth fellowship supported by British Council tenable at the Centre for Entomology and Parasitology (CAEP), Keele University, United Kingdom between 2004 and 2005. She was awarded an Honorary Visiting Research Fellow at the same university from 2005 to 2007. \nShe has been an external examiner to the Department of Veterinary Microbiology and Parasitology, University of Ibadan, MSc programme between 2010 and 2012. She is a member of the Nigerian Society of Experimental Biology (NISEB), Parasitology and Public Health Society of Nigeria (PPSN), Science Association of Nigeria (SAN), Zoological Society of Nigeria (ZSN), and is Vice Chairperson of the Organisation of Women in Science (OWSG), LASU chapter. She served as Head of Department of Zoology and Environmental Biology, Lagos State University from 2007 to 2010 and 2014 to 2016. She is a reviewer for several local and international journals such as Unilag Journal of Science, Libyan Journal of Medicine, Journal of Medicine and Medical Sciences, and Annual Research and Review in Science. \nShe has authored 45 scientific research publications in local and international journals, 8 scientific reviews, 4 books, and 3 book chapters, which includes the books “Malaria Parasites” and “Malaria” which are IntechOpen access publications.",institutionString:"Lagos State University",institution:{name:"Lagos State University",country:{name:"Nigeria"}}},{id:"273100",title:"Dr.",name:"Vijay",middleName:null,surname:"Gayam",slug:"vijay-gayam",fullName:"Vijay Gayam",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/273100/images/system/273100.jpeg",biography:"Dr. Vijay Bhaskar Reddy Gayam is currently practicing as an internist at Interfaith Medical Center in Brooklyn, New York, USA. He is also a Clinical Assistant Professor at the SUNY Downstate University Hospital and Adjunct Professor of Medicine at the American University of Antigua. He is a holder of an M.B.B.S. degree bestowed to him by Osmania Medical College and received his M.D. at Interfaith Medical Center. His career goals thus far have heavily focused on direct patient care, medical education, and clinical research. He currently serves in two leadership capacities; Assistant Program Director of Medicine at Interfaith Medical Center and as a Councilor for the American\r\nFederation for Medical Research. As a true academician and researcher, he has more than 50 papers indexed in international peer-reviewed journals. He has also presented numerous papers in multiple national and international scientific conferences. His areas of research interest include general internal medicine, gastroenterology and hepatology. He serves as an editor, editorial board member and reviewer for multiple international journals. His research on Hepatitis C has been very successful and has led to multiple research awards, including the 'Equity in Prevention and Treatment Award” from the New York Department of Health Viral Hepatitis Symposium (2018) and the 'Presidential Poster Award” awarded to him by the American College of Gastroenterology (2018). He was also awarded 'Outstanding Clinician in General Medicine” by Venus International Foundation for his extensive research expertise and services, perform over and above the standard expected in the advancement of healthcare, patient safety and quality of care.",institutionString:"Interfaith Medical Center",institution:{name:"Interfaith Medical Center",country:{name:"United States of America"}}},{id:"93517",title:"Dr.",name:"Clement",middleName:"Adebajo",surname:"Meseko",slug:"clement-meseko",fullName:"Clement Meseko",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/93517/images/system/93517.jpg",biography:"Dr. Clement Meseko obtained DVM and PhD degree in Veterinary Medicine and Virology respectively. He has worked for over 20 years in both private and public sectors including the academia, contributing to knowledge and control of infectious disease. Through the application of epidemiological skill, classical and molecular virological skills, he investigates viruses of economic and public health importance for the mitigation of the negative impact on people, animal and the environment in the context of Onehealth. \r\nDr. Meseko’s field experience on animal and zoonotic diseases and pathogen dynamics at the human-animal interface over the years shaped his carrier in research and scientific inquiries. He has been part of the investigation of Highly Pathogenic Avian Influenza incursions in sub Saharan Africa and monitors swine Influenza (Pandemic influenza Virus) agro-ecology and potential for interspecies transmission. He has authored and reviewed a number of journal articles and book chapters.",institutionString:"National Veterinary Research Institute",institution:{name:"National Veterinary Research Institute",country:{name:"Nigeria"}}},{id:"158026",title:"Prof.",name:"Shailendra K.",middleName:null,surname:"Saxena",slug:"shailendra-k.-saxena",fullName:"Shailendra K. Saxena",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRET3QAO/Profile_Picture_2022-05-10T10:10:26.jpeg",biography:"Professor Dr. Shailendra K. Saxena is a vice dean and professor at King George's Medical University, Lucknow, India. His research interests involve understanding the molecular mechanisms of host defense during human viral infections and developing new predictive, preventive, and therapeutic strategies for them using Japanese encephalitis virus (JEV), HIV, and emerging viruses as a model via stem cell and cell culture technologies. His research work has been published in various high-impact factor journals (Science, PNAS, Nature Medicine) with a high number of citations. He has received many awards and honors in India and abroad including various Young Scientist Awards, BBSRC India Partnering Award, and Dr. JC Bose National Award of Department of Biotechnology, Min. of Science and Technology, Govt. of India. Dr. Saxena is a fellow of various international societies/academies including the Royal College of Pathologists, United Kingdom; Royal Society of Medicine, London; Royal Society of Biology, United Kingdom; Royal Society of Chemistry, London; and Academy of Translational Medicine Professionals, Austria. He was named a Global Leader in Science by The Scientist. He is also an international opinion leader/expert in vaccination for Japanese encephalitis by IPIC (UK).",institutionString:"King George's Medical University",institution:{name:"King George's Medical University",country:{name:"India"}}},{id:"94928",title:"Dr.",name:"Takuo",middleName:null,surname:"Mizukami",slug:"takuo-mizukami",fullName:"Takuo Mizukami",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/94928/images/6402_n.jpg",biography:null,institutionString:null,institution:{name:"National Institute of Infectious Diseases",country:{name:"Japan"}}},{id:"233433",title:"Dr.",name:"Yulia",middleName:null,surname:"Desheva",slug:"yulia-desheva",fullName:"Yulia Desheva",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/233433/images/system/233433.png",biography:"Dr. Yulia Desheva is a leading researcher at the Institute of Experimental Medicine, St. Petersburg, Russia. She is a professor in the Stomatology Faculty, St. Petersburg State University. She has expertise in the development and evaluation of a wide range of live mucosal vaccines against influenza and bacterial complications. Her research interests include immunity against influenza and COVID-19 and the development of immunization schemes for high-risk individuals.",institutionString:'Federal State Budgetary Scientific Institution "Institute of Experimental Medicine"',institution:null},{id:"238958",title:"Mr.",name:"Atamjit",middleName:null,surname:"Singh",slug:"atamjit-singh",fullName:"Atamjit Singh",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/238958/images/6575_n.jpg",biography:null,institutionString:null,institution:null},{id:"252058",title:"M.Sc.",name:"Juan",middleName:null,surname:"Sulca",slug:"juan-sulca",fullName:"Juan Sulca",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/252058/images/12834_n.jpg",biography:null,institutionString:null,institution:null},{id:"191392",title:"Dr.",name:"Marimuthu",middleName:null,surname:"Govindarajan",slug:"marimuthu-govindarajan",fullName:"Marimuthu Govindarajan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/191392/images/5828_n.jpg",biography:"Dr. M. Govindarajan completed his BSc degree in Zoology at Government Arts College (Autonomous), Kumbakonam, and MSc, MPhil, and PhD degrees at Annamalai University, Annamalai Nagar, Tamil Nadu, India. He is serving as an assistant professor at the Department of Zoology, Annamalai University. His research interests include isolation, identification, and characterization of biologically active molecules from plants and microbes. He has identified more than 20 pure compounds with high mosquitocidal activity and also conducted high-quality research on photochemistry and nanosynthesis. He has published more than 150 studies in journals with impact factor and 2 books in Lambert Academic Publishing, Germany. He serves as an editorial board member in various national and international scientific journals.",institutionString:null,institution:null},{id:"274660",title:"Dr.",name:"Damodar",middleName:null,surname:"Paudel",slug:"damodar-paudel",fullName:"Damodar Paudel",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/274660/images/8176_n.jpg",biography:"I am DrDamodar Paudel,currently working as consultant Physician in Nepal police Hospital.",institutionString:null,institution:null},{id:"241562",title:"Dr.",name:"Melvin",middleName:null,surname:"Sanicas",slug:"melvin-sanicas",fullName:"Melvin Sanicas",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241562/images/6699_n.jpg",biography:null,institutionString:null,institution:null},{id:"322007",title:"Dr.",name:"Maria Elizbeth",middleName:null,surname:"Alvarez-Sánchez",slug:"maria-elizbeth-alvarez-sanchez",fullName:"Maria Elizbeth Alvarez-Sánchez",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Universidad Autónoma de la Ciudad de México",country:{name:"Mexico"}}},{id:"337443",title:"Dr.",name:"Juan",middleName:null,surname:"A. Gonzalez-Sanchez",slug:"juan-a.-gonzalez-sanchez",fullName:"Juan A. Gonzalez-Sanchez",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Puerto Rico System",country:{name:"United States of America"}}},{id:"337446",title:"Dr.",name:"Maria",middleName:null,surname:"Zavala-Colon",slug:"maria-zavala-colon",fullName:"Maria Zavala-Colon",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Puerto Rico, Medical Sciences Campus",country:{name:"United States of America"}}},{id:"338856",title:"Mrs.",name:"Nur Alvira",middleName:null,surname:"Pascawati",slug:"nur-alvira-pascawati",fullName:"Nur Alvira Pascawati",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Universitas Respati Yogyakarta",country:{name:"Indonesia"}}}]}},subseries:{item:{id:"94",type:"subseries",title:"Climate Change and Environmental Sustainability",keywords:"Environmental Protection, Socio-economic Development, Resource Exploitation, Environmental Degradation, Climate Change, Degraded Ecosystems, Biodiversity Loss",scope:"\r\n\tSustainable development focuses on linking economic development with environmental protection and social development to ensure future prosperity for people and the planet. To tackle global challenges of development and environment, the United Nations General Assembly in 2015 adopted the 17 Sustainable Development Goals. SDGs emphasize that environmental sustainability should be strongly linked to socio-economic development, which should be decoupled from escalating resource use and environmental degradation for the purpose of reducing environmental stress, enhancing human welfare, and improving regional equity. Moreover, sustainable development seeks a balance between human development and decrease in ecological/environmental marginal benefits. Under the increasing stress of climate change, many environmental problems have emerged causing severe impacts at both global and local scales, driving ecosystem service reduction and biodiversity loss. Humanity’s relationship with resource exploitation and environment protection is a major global concern, as new threats to human and environmental security emerge in the Anthropocene. Currently, the world is facing significant challenges in environmental sustainability to protect global environments and to restore degraded ecosystems, while maintaining human development with regional equality. Thus, environmental sustainability with healthy natural ecosystems is critical to maintaining human prosperity in our warming planet.
",coverUrl:"https://cdn.intechopen.com/series_topics/covers/94.jpg",hasOnlineFirst:!0,hasPublishedBooks:!1,annualVolume:11978,editor:{id:"61855",title:"Dr.",name:"Yixin",middleName:null,surname:"Zhang",slug:"yixin-zhang",fullName:"Yixin Zhang",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYWJgQAO/Profile_Picture_2022-06-09T11:36:35.jpg",biography:"Professor Yixin Zhang is an aquatic ecologist with over 30 years of research and teaching experience in three continents (Asia, Europe, and North America) in Stream Ecology, Riparian Ecology, Urban Ecology, and Ecosystem Restoration and Aquatic Conservation, Human-Nature Interactions and Sustainability, Urbanization Impact on Aquatic Ecosystems. He got his Ph.D. in Animal Ecology at Umeå University in Sweden in 1998. He conducted postdoc research in stream ecology at the University of California at Santa Barbara in the USA. 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