Books.org participates in affiliate programs including Bookshop.org and the Amazon Services LLC Associates Program. We may earn a commission from qualifying purchases made through links on this page, at no additional cost to you.
Synopsis
Evolutionary algorithms are relatively new, but very powerful techniques used to find solutions to many real-world search and optimization problems. Many of these problems have multiple objectives, which leads to the need to obtain a set of optimal solutions, known as effective solutions. It has been found that using evolutionary algorithms is a highly effective way of finding multiple effective solutions in a single simulation run.
* Comprehensive coverage of this growing area of research
* Carefully introduces each algorithm with examples and in-depth discussion
* Includes many applications to real-world problems, including engineering design and scheduling
* Includes discussion of advanced topics and future research
* Can be used as a course text or for self-study
* Accessible to those with limited knowledge of classical multi-objective optimization and evolutionary algorithms
The integrated presentation of theory, algorithms and examples will benefit those working and researching in the areas of optimization, optimal design and evolutionary computing. This text provides an excellent introduction to the use of evolutionary algorithms in multi-objective optimization, allowing use as a graduate course text or for self-study.
Booknews
This book provides an integrated treatment of the theory and carefully introduces each algorithm with examples and detailed explication. Applications to engineering, design, and scheduling are emphasized. Intended as a textbook or self-study guide, the book assumes limited prior knowledge of the topics, but is intended to be useful to researchers working on optimization, optimal design, and evolutionary computing. Deb teaches mechanical engineering at the Indian Institute of Technology. Annotation c. Book News, Inc., Portland, OR (booknews.com)