Open access peer-reviewed chapter

Genetic Algorithm-Based Approaches for Solving Inexact Optimization Problems and their Applications for Municipal Solid Waste Management

By Weihua Jin, Zhiying Hu and Christine W. Chan

Submitted: October 13th 2015Reviewed: February 11th 2016Published: September 21st 2016

DOI: 10.5772/62475

Downloaded: 550

© 2016 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution 3.0 License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to cite and reference

Link to this chapter Copy to clipboard

Cite this chapter Copy to clipboard

Weihua Jin, Zhiying Hu and Christine W. Chan (September 21st 2016). Genetic Algorithm-Based Approaches for Solving Inexact Optimization Problems and their Applications for Municipal Solid Waste Management, Optimization Algorithms Ozgur Baskan, IntechOpen, DOI: 10.5772/62475. Available from:

Embed this chapter on your site Copy to clipboard

<iframe src="http://www.intechopen.com/embed/optimization-algorithms-methods-and-applications/genetic-algorithm-based-approaches-for-solving-inexact-optimization-problems-and-their-applications-" />

Embed this code snippet in the HTML of your website to show this chapter

chapter statistics

550total chapter downloads

More statistics for editors and authors

Login to your personal dashboard for more detailed statistics on your publications.

Access personal reporting

Related Content

This Book

Next chapter

Optimization Algorithms for Chemoinformatics and Material-informatics

By Abraham Yosipof and Hanoch Senderowitz

Related Book

First compact

Introductory Chapter: Nature-Inspired Methods for Stochastic, Robust, and Dynamic Optimization

By Eneko Osaba and Javier Del Ser

We are IntechOpen, the world's leading publisher of Open Access books. Built by scientists, for scientists. Our readership spans scientists, professors, researchers, librarians, and students, as well as business professionals. We share our knowledge and peer-reveiwed research papers with libraries, scientific and engineering societies, and also work with corporate R&D departments and government entities.

+3,550 Open Access Books

+57,400 Citations in Web of Science

+108,500 IntechOpen Authors and Academic Editors

+560,000 Unique visitors per month

More about us