Representations for Genetic and Evolutionary Algorithms

✍ Scribed by Dr. Franz Rothlauf (auth.)

Publisher: Physica-Verlag Heidelberg
Year: 2002
Tongue: English
Leaves: 294
Series: Studies in Fuzziness and Soft Computing 104
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

In the field of genetic and evolutionary algorithms (GEAs), much theory and empirical study has been heaped upon operators and test problems, but problem representation has often been taken as given. This monograph breaks with this tradition and studies a number of critical elements of a theory of representations for GEAs and applies them to the empirical study of various important idealized test functions and problems of commercial import. The book considers basic concepts of representations, such as redundancy, scaling and locality and describes how GEAs'performance is influenced. Using the developed theory representations can be analyzed and designed in a theory-guided manner. The theoretical concepts are used as examples for efficiently solving integer optimization problems and network design problems. The results show that proper representations are crucial for GEAs'success.

✦ Table of Contents

Front Matter....Pages I-XIV
Introduction....Pages 1-7
Representations for Genetic and Evolutionary Algorithms....Pages 9-30
Three Elements of a Theory of Genetic and Evolutionary Representations....Pages 31-75
Time-Quality Framework for a Theory-Based Analysis and Design of Representations....Pages 77-97
Analysis of Binary Representations of Integers....Pages 99-118
Analysis of Tree Representations....Pages 119-176
Design of Tree Representations....Pages 177-197
Performance of Genetic and Evolutionary Algorithms on Tree Problems....Pages 199-236
Summary, Conclusions and Future Work....Pages 237-243
Optimal Communication Spanning Tree Test Instances....Pages 245-261
Back Matter....Pages 263-290

✦ Subjects

Artificial Intelligence (incl. Robotics); Appl.Mathematics/Computational Methods of Engineering; Operations Research/Decision Theory; Operations Research, Management Science

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