Multi-objective optimization using evolutionary algorithms / Kalyanmoy Deb.
By: Deb, Kalyanmoy.
Material type:
BookPublisher: [S.l.] : Wiley, 2005Edition: 1st ed.Description: 544 p. ; 25 cm.ISBN: 0470743611 (paperback); 9780470743614 (paperback).Online resources: Amazon.com Summary: The Wiley Paperback Series makes valuable content more accessible to a new generation of statisticians, mathematicians and scientists. 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. Comrephensive 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. 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.
| Item type | Current location | Call number | Status | Date due | Barcode | Item holds |
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Books
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Central Library, QUEST, Nawabshah
Welcome to the Central Library, QUEST, Nawabshah, Sindh, Pakistan |
519.3DEB (Browse shelf) | Available | 32597 | ||
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Books
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Central Library, QUEST, Nawabshah
Welcome to the Central Library, QUEST, Nawabshah, Sindh, Pakistan |
519.3DEB (Browse shelf) | Available | 32598 |
The Wiley Paperback Series makes valuable content more accessible to a new generation of statisticians, mathematicians and scientists. 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. Comrephensive 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. 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.
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