Description

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.

  1. Comrephensive coverage of this growing area of research.
  2. Carefully introduces each algorithm with examples and in-depth discussion.
  3. Includes many applications to real-world problems, including engineering design and scheduling.
  4. Includes discussion of advanced topics and future research.
  5. 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.

Multi-Objective Optimization Using Evolutionary Algorithms

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£63.95

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Paperback / softback by Kalyanmoy Deb

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Short Description:

The Wiley Paperback Series makes valuable content more accessible to a new generation of statisticians, mathematicians and scientists. Evolutionary algorithms... Read more

    Publisher: John Wiley & Sons Inc
    Publication Date: 28/10/2008
    ISBN13: 9780470743614, 978-0470743614
    ISBN10: 0470743611

    Number of Pages: 544

    Non Fiction , Mathematics & Science , Education

    Description

    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.

    1. Comrephensive coverage of this growing area of research.
    2. Carefully introduces each algorithm with examples and in-depth discussion.
    3. Includes many applications to real-world problems, including engineering design and scheduling.
    4. Includes discussion of advanced topics and future research.
    5. 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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