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Genetic Algorithms + Data Structures = Evolution Programs

  • Book
  • © 1996

Overview

Authors:
  1. Zbigniew Michalewicz

    1. Department of Computer Science, University of North Carolina, Charlotte, USA

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  • Classic introduction to the evolution programming techniques
  • Many figures and tables
  • The systematic approach makes the book an appropriate text for a senior undergraduate/graduate one semester course

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Table of contents (17 chapters)

  1. Front Matter

    Pages I-XX
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  2. Introduction

    1. Introduction

      • Zbigniew Michalewicz
      Pages 1-10

  3. Genetic Algorithms

    1. Front Matter

      Pages 11-11
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    2. GAs: What Are They?

      • Zbigniew Michalewicz
      Pages 13-31

    3. GAs: How Do They Work?

      • Zbigniew Michalewicz
      Pages 33-44

    4. GAs: Why Do They Work?

      • Zbigniew Michalewicz
      Pages 45-55

    5. GAs: Selected Topics

      • Zbigniew Michalewicz
      Pages 57-93

  4. Numerical Optimization

    1. Front Matter

      Pages 95-95
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    2. Binary or Float?

      • Zbigniew Michalewicz
      Pages 97-106

    3. Fine Local Tuning

      • Zbigniew Michalewicz
      Pages 107-120

    4. Handling Constraints

      • Zbigniew Michalewicz
      Pages 121-157

    5. Evolution Strategies and Other Methods

      • Zbigniew Michalewicz
      Pages 159-177

  5. Evolution Programs

    1. Front Matter

      Pages 179-179
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    2. The Transportation Problem

      • Zbigniew Michalewicz
      Pages 181-208

    3. The Traveling Salesman Problem

      • Zbigniew Michalewicz
      Pages 209-237

    4. Evolution Programs for Various Discrete Problems

      • Zbigniew Michalewicz
      Pages 239-266

    5. Machine Learning

      • Zbigniew Michalewicz
      Pages 267-281

    6. Evolutionary Programming and Genetic Programming

      • Zbigniew Michalewicz
      Pages 283-287

    7. A Hierarchy of Evolution Programs

      • Zbigniew Michalewicz
      Pages 289-306

    8. Evolution Programs and Heuristics

      • Zbigniew Michalewicz
      Pages 307-327
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Keywords

About this book

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.

Authors and Affiliations

  • Department of Computer Science, University of North Carolina, Charlotte, USA

    Zbigniew Michalewicz

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