Representations for Genetic and Evolutionary Algorithms

By: Franz Rothlauf

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Hardcover | 10 January 2006 | Edition Number 2

At a Glance

Hardcover
344 Pages

Edition Type
Revised

Dimensions(cm)
24.77 x 17.15 x 2.54

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In the field of genetic and evolutionary algorithms (GEAs), a large amount of theory and empirical study has been focused on operators and test problems, while problem representation has often been taken as given. This book breaks with this tradition and provides a comprehensive overview on the influence of problem representations on GEA performance. The book summarizes existing knowledge regarding problem representations and describes how basic properties of representations, such as redundancy, scaling, or locality, influence the performance of GEAs and other heuristic optimization methods. Using the developed theory, representations can be analyzed and designed in a theory-guided matter. The theoretical concepts are used for solving integer optimization problems and network design problems more efficiently. The book is written in an easy-readable style and is intended for researchers, practitioners, and students who want to learn about representations. This second edition extends the analysis of the basic properties of representations and introduces a new chapter on the analysis of direct representations.

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Introduction	p. 1
Representations for genetic and evolutionary algorithms	p. 9
Three elements of a theory of representations	p. 33
Time-quality framework for a theory-based analysis and design of representations	p. 97
Analysis of binary representations of integers	p. 117
Analysis and design of representations for trees	p. 141
Analysis and design of search operators for trees	p. 217
Performance of genetic and evolutionary algorithms on tree problems	p. 241
Summary and conclusions	p. 275
Optimal communication spanning tree test instances	p. 281
Table of Contents provided by Blackwell. All Rights Reserved.

Representations for Genetic and Evolutionary Algorithms

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Hardcover

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