Multi-Objective Optimization using Evolutionary Algorithms (Wiley Interscience Series in Systems and Optimization)

Multi-Objective Optimization using Evolutionary Algorithms (Wiley Interscience Series in Systems and Optimization)

By: Kalyanmoy Deb (author)Paperback

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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.


Foreword. Preface. Prologue. Multi-Objective Optimization. Classical Methods. Evolutionary Algorithms. Non-Elitist Multi-Objective Evolutionary Algorithms. Elitist Multi-Objective Evolutionary Algorithms. Constrained Multi-Objective Evolutionary Algorithms. Salient Issues of Multi-Objective Evolutionary Algorithms. Applications of Multi-Objective Evolutionary Algorithms. Epilogue. References. Index.

Product Details

  • ISBN13: 9780470743614
  • Format: Paperback
  • Number Of Pages: 544
  • ID: 9780470743614
  • weight: 938
  • ISBN10: 0470743611

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