multi objective optimization using evolutionary de deb kalyanmoy (46 résultats)

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Paperback. Etat : new. Paperback. 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. 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. Accessible to those with limited knowledge of multi-objective optimization and evolutionary algorithms. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Paperback. Etat : New. 1st. 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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Etat : New. 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. Accessible to those with limited knowledge of multi-objective optimization and evolutionary algorithms. Num Pages: 544 pages, black & white illustrations, black & white tables, maps, figures. BIC Classification: PBW. Category: (P) Professional & Vocational. Dimension: 242 x 170 x 29. Weight in Grams: 868. . 2009. 1st Edition. Paperback. . . . .

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Paperback. Etat : new. Paperback. 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. 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. Accessible to those with limited knowledge of multi-objective optimization and evolutionary algorithms. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Etat : New. 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. Accessible to those with limited knowledge of multi-objective optimization and evolutionary algorithms. Num Pages: 544 pages, black & white illustrations, black & white tables, maps, figures. BIC Classification: PBW. Category: (P) Professional & Vocational. Dimension: 242 x 170 x 29. Weight in Grams: 868. . 2009. 1st Edition. Paperback. . . . . Books ship from the US and Ireland.

Kartoniert / Broschiert. Etat : New. Multi-Objective Optimization using Evolutionary AlgorithmsKalyanmoy DebIndian Institute of Technology, Kanpur, IndiaThe Wiley Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal.

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Paperback. Etat : new. Paperback. 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. 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. Accessible to those with limited knowledge of multi-objective optimization and evolutionary algorithms. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

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Taschenbuch. Etat : Neu. Neuware - 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 algorithmsProvides 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.

Paperback. Etat : New. 1st. 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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