Multi-Objective Optimization Using

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Evolutionary algorithms are very powerful techniques used to find solutions to 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.

1. Comrephensive coverage of this growing area of research.
2. Carefully introduces each algorithm with examples and in-depth discussion.
3. Includes many applications to real-world problems, including engineering design and scheduling.
4. Includes discussion of advanced topics and future research.
5. Accessible to those with limited knowledge of multi-objective optimization and evolutionary algorithms

Provides an extensive discussion on the principles of multi-objective optimization and on a number of classical approaches.

This integrated presentation of theory, algorithms and examples will benefit those working in the areas of optimization, optimal design and evolutionary computing.

Author: Deb
Publisher: John Wiley & Sons
Published: 03/01/2009
Pages: 544
Binding Type: Paperback
Weight: 1.95lbs
Size: 9.40h x 6.50w x 1.20d
ISBN13: 9780470743614
ISBN10: 0470743611
BISAC Categories:
- Mathematics | Applied

About the Author

Kalyanmoy Deb is an Indian computer scientist. Since 2013, Deb has held the Herman E. & Ruth J. Koenig Endowed Chair in the Department of Electrical and Computing Engineering at Michigan State University, which was established in 2001.