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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.
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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.
From the Back Cover
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.
- Comprehensive coverage of...
From the Inside Flap
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.
- Comprehensive coverage of...
"About this title" may belong to another edition of this title.
- PublisherWiley
- Publication date2001
- ISBN 10 047187339X
- ISBN 13 9780471873396
- BindingHardcover
- LanguageEnglish
- Edition number1
- Number of pages536
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Multi-Objective Optimization using Evolutionary Algorithms (Hardcover)
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John Wiley & Sons Inc, New York, 2001
ISBN 10: 047187339X
ISBN 13: 9780471873396
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Hardcover. Condition: new. Hardcover. 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 researchCarefully introduces each algorithm with examples and in-depth discussionIncludes many applications to real-world problems, including engineering design and schedulingIncludes discussion of advanced topics and future researchCan be used as a course text or for self-studyAccessible 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. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9780471873396
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Multi-Objective Optimization Using Evolutionary Algorithms
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