Multi-objective Optimization Using Evolutionary Algorithms

Kalyanmoy Deb

ISBN 10: 047187339X / ISBN 13: 9780471873396

Published by John Wiley and Sons Ltd, 2001

About this Item

Evolutionary algorithms are relatively new, powerful techniques used to find solutions to many real--world search and optimization problems. Focusing on these "thinking" algorithms, this book offers comprehensive coverage of these techniques, which are highly effective in finding multiple effective solutions in a single simulation run. Series: Wiley Interscience Series in Systems & Optimization. Num Pages: 518 pages, Ill. BIC Classification: PBU; PBW; PSAJ. Category: (P) Professional & Vocational. Dimension: 250 x 175 x 40. Weight in Grams: 1110. . 2001. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.

Seller Inventory # V9780471873396

Bibliographic Details

• Title: Multi-objective Optimization Using Evolutionary Algorithms
• Publisher: John Wiley and Sons Ltd
• Publication Date: 2001
• Language: English
• ISBN 10: 047187339X
• ISBN 13: 9780471873396
• Binding: Hardcover
• Condition: New

About this title

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.

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.