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Evolutionary Optimization

  • Book
  • © 2002

Overview

Authors:
  1. Ruhul Sarker

    1. University of New South Wales, Australia

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    You can also search for this author in PubMed   Google Scholar

  2. Masoud Mohammadian

    1. University of Canberra, Australia

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    You can also search for this author in PubMed   Google Scholar

  3. Xin Yao

    1. University of Birmingham, UK

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    You can also search for this author in PubMed   Google Scholar

Part of the book series: International Series in Operations Research & Management Science (ISOR, volume 48)

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Table of contents (16 chapters)

  1. Front Matter

    Pages i-xiv
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  2. Introduction

    1. Front Matter

      Pages 1-1
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    2. Conventional Optimization Techniques

      • Mark S. Hillier, Frederick S. Hillier
      Pages 3-25

    3. Evolutionary Computation

      • Xin Yao
      Pages 27-53

  3. Single Objective Optimization

    1. Front Matter

      Pages 55-55
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    2. Evolutionary Algorithms and Constrained Optimization

      • Zbigniew Michalewicz, Martin Schmidt
      Pages 57-86

    3. Constrained Evolutionary Optimization

      • Thomas Runarsson, Xin Yao
      Pages 87-113

  4. Multi-Objective Optimization

    1. Front Matter

      Pages 115-115
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    2. Evolutionary Multi-Objective Optimization: A Critical Review

      • Carlos A. Coello Coello
      Pages 117-146

    3. Multi-Objective Evolutionary Algorithms for Engineering Shape Design

      • Kalyanmoy Deb, Tushar Goel
      Pages 147-175

    4. Assessment Methodologies for Multiobjective Evolutionary Algorithms

      • Ruhul Sarker, Carlos A. Coello Coello
      Pages 177-195

  5. Hybrid Algorithms

    1. Front Matter

      Pages 197-197
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    2. Utilizing Hybrid Genetic Algorithms

      • Jeffrey A. Joines, Michael G. Kay
      Pages 199-228

    3. Using Evolutionary Algorithms to Solve Problems by Combining Choices of Heuristics

      • Peter Ross, Emma Hart
      Pages 229-252

    4. Constrained Genetic Algorithms and Their Applications in Nonlinear Constrained Optimization

      • Benjamin W. Wah, Yi-Xin Chen
      Pages 253-275

  6. Parameter Selection in EAs

    1. Front Matter

      Pages 277-277
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    2. Parameter Selection

      • Zbigniew Michalewicz, Ágoston E. Eiben, Robert Hinterding
      Pages 279-306

  7. Application of EAs to Practical Problems

    1. Front Matter

      Pages 307-307
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    2. Design of Production Facilities Using Evolutionary Computing

      • Alice E. Smith, Bryan A. Norman
      Pages 309-327

    3. Virtual Population and Acceleration Techniques for Evolutionary Power Flow Calculation in Power Systems

      • Kit Po Wong, An Li
      Pages 329-345
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Keywords

About this book

Evolutionary computation techniques have attracted increasing att- tions in recent years for solving complex optimization problems. They are more robust than traditional methods based on formal logics or mathematical programming for many real world OR/MS problems. E- lutionary computation techniques can deal with complex optimization problems better than traditional optimization techniques. However, most papers on the application of evolutionary computation techniques to Operations Research /Management Science (OR/MS) problems have scattered around in different journals and conference proceedings. They also tend to focus on a very special and narrow topic. It is the right time that an archival book series publishes a special volume which - cludes critical reviews of the state-of-art of those evolutionary com- tation techniques which have been found particularly useful for OR/MS problems, and a collection of papers which represent the latest devel- ment in tackling various OR/MS problems by evolutionary computation techniques. This special volume of the book series on Evolutionary - timization aims at filling in this gap in the current literature. The special volume consists of invited papers written by leading - searchers in the field. All papers were peer reviewed by at least two recognised reviewers. The book covers the foundation as well as the practical side of evolutionary optimization.

Reviews

From the reviews:

"The book contains 17 chapters written by leading experts in evolutionary computation. … Of special value is the analysis of evolutionary algorithms on pseudo-Boolean functions, given by Ingo Wegener. He and his coauthors are the first, who proved substantially sharp results on the expected run time and the success probability for evolutionary algorithms with (respectively without) crossover, giving sharp upper and lower bounds." (Hartmut Noltemeier, Zentralblatt MATH, Vol. 1072 (23), 2005)

Authors and Affiliations

  • University of New South Wales, Australia

    Ruhul Sarker

  • University of Canberra, Australia

    Masoud Mohammadian

  • University of Birmingham, UK

    Xin Yao

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