Multi-Objective Optimization Using Evolutionary Algorithms

Multi-Objective Optimization Using Evolutionary Algorithms (English, Paperback, Deb Kalyanmoy)

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Multi-Objective Optimization Using Evolutionary Algorithms  (English, Paperback, Deb Kalyanmoy)

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    Highlights
    • Language: English
    • Binding: Paperback
    • Publisher: John Wiley & Sons Inc
    • Genre: Science
    • ISBN: 9780470743614, 9780470743614
    • Pages: 544
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  • 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. 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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    Book Details
    Imprint
    • John Wiley & Sons Inc
    Dimensions
    Width
    • 30 mm
    Height
    • 248 mm
    Length
    • 172 mm
    Weight
    • 879 gr
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    Ratings & Reviews
    4.2
    37 Ratings &
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    5

    NSGA I-II Father.. really a book of researcher

    Best book out there available for solving multi-objective optimization problems in really a simple efficient manner using genetic approaches and his research algorithm NSGA, crowding, and non-dominated fast sorting.
    All the algorithms given are hand-solved also by the author so that one can see the working also, diagrams are way good to understand the theory and idea behind the method.
    Can't say much .. it's good must have for a good research in this direction..
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    Piyush Chauhan

    Jun, 2012

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