© 2002

Evolutionary Optimization


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

Table of contents

  1. Front Matter
    Pages i-xiv
  2. Introduction

    1. Front Matter
      Pages 1-1
    2. Mark S. Hillier, Frederick S. Hillier
      Pages 3-25
    3. Xin Yao
      Pages 27-53
  3. Single Objective Optimization

    1. Front Matter
      Pages 55-55
    2. Zbigniew Michalewicz, Martin Schmidt
      Pages 57-86
    3. Thomas Runarsson, Xin Yao
      Pages 87-113
  4. Multi-Objective Optimization

    1. Front Matter
      Pages 115-115
    2. Carlos A. Coello Coello
      Pages 117-146
    3. Ruhul Sarker, Carlos A. Coello Coello
      Pages 177-195
  5. Hybrid Algorithms

    1. Front Matter
      Pages 197-197
    2. Jeffrey A. Joines, Michael G. Kay
      Pages 199-228
  6. Parameter Selection in EAs

    1. Front Matter
      Pages 277-277
    2. Zbigniew Michalewicz, Ágoston E. Eiben, Robert Hinterding
      Pages 279-306
  7. Application of EAs to Practical Problems

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.


algorithms evolutionary algorithm formal logic genetic algorithms heuristics intelligence multi-objective optimization optimization programming

Authors and affiliations

  1. 1.University of New South WalesAustralia
  2. 2.University of CanberraAustralia
  3. 3.University of BirminghamUK

Bibliographic information


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)