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Genetic Algorithms + Data Structures = Evolution Programs

  • Zbigniew¬†Michalewicz

Table of contents

  1. Front Matter
    Pages I-XX
  2. Introduction

    1. Zbigniew Michalewicz
      Pages 1-10
  3. Genetic Algorithms

    1. Front Matter
      Pages 11-11
    2. Zbigniew Michalewicz
      Pages 13-31
    3. Zbigniew Michalewicz
      Pages 33-44
    4. Zbigniew Michalewicz
      Pages 45-55
    5. Zbigniew Michalewicz
      Pages 57-93
  4. Numerical Optimization

    1. Front Matter
      Pages 95-95
    2. Zbigniew Michalewicz
      Pages 97-106
    3. Zbigniew Michalewicz
      Pages 107-120
    4. Zbigniew Michalewicz
      Pages 121-157
    5. Zbigniew Michalewicz
      Pages 159-177
  5. Evolution Programs

    1. Front Matter
      Pages 179-179
    2. Zbigniew Michalewicz
      Pages 181-208
    3. Zbigniew Michalewicz
      Pages 209-237
    4. Zbigniew Michalewicz
      Pages 239-266
    5. Zbigniew Michalewicz
      Pages 267-281
    6. Zbigniew Michalewicz
      Pages 283-287
    7. Zbigniew Michalewicz
      Pages 289-306
    8. Zbigniew Michalewicz
      Pages 307-327
    9. Zbigniew Michalewicz
      Pages 329-336
  6. Back Matter
    Pages 337-387

About this book

Introduction

Genetic algorithms are founded upon the principle of evolution, i.e., survival of the fittest. Hence evolution programming techniques, based on genetic algorithms, are applicable to many hard optimization problems, such as optimization of functions with linear and nonlinear constraints, the traveling salesman problem, and problems of scheduling, partitioning, and control. The importance of these techniques is still growing, since evolution programs are parallel in nature, and parallelism is one of the most promising directions in computer science.
The book is self-contained and the only prerequisite is basic undergraduate mathematics. This third edition has been substantially revised and extended by three new chapters and by additional appendices containing working material to cover recent developments and a change in the perception of evolutionary computation.

Keywords

Optimierung Suchalgorithmen algorithms data structures evolutionary computation genetic algorithms genetic programming heuristics learning machine learning optimization probabilistic algorithms probabilistische Algorithmen programming search techniques

Authors and affiliations

  • Zbigniew¬†Michalewicz
    • 1
  1. 1.Department of Computer ScienceUniversity of North CarolinaCharlotteUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-662-03315-9
  • Copyright Information Springer-Verlag Berlin Heidelberg 1996
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-642-08233-7
  • Online ISBN 978-3-662-03315-9
  • Buy this book on publisher's site