Multi-objective Optimization Using Evolutionary Algorithms
Kalyanmoy Deb
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Description for Multi-objective Optimization Using Evolutionary Algorithms
Hardcover. 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.
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.
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 ... Read more
- 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.
Show LessProduct Details
Format
Hardback
Publication date
2001
Publisher
John Wiley and Sons Ltd United Kingdom
Number of pages
518
Condition
New
Series
Wiley Interscience Series in Systems & Optimization
Number of Pages
536
Place of Publication
New York, United States
ISBN
9780471873396
SKU
V9780471873396
Shipping Time
Usually ships in 7 to 11 working days
Ref
99-50
About Kalyanmoy Deb
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.
Reviews for Multi-objective Optimization Using Evolutionary Algorithms
"Deb's book is complete, eminently readable, and the coverage is scholarly and thorough. It is my pleasure and duty to urge you to buy this book, read it, use it and enjoy it." (David E. Goldberg, University of Illinois at Urbana-Champaign, USA) "...discusses two multi-objective optimization procedures, namely the ideal procedure and the preference-based one." (Zentralblatt MATH, Vol. 970, ... Read more