An Analysis of the Intensification and Diversification Behavior of Different Operators for Genetic Algorithms

Intensification and diversification are two driving forces in genetic algorithms and are frequently the subject of research. While it seemed for decades that a genetic operator can be classified as either the one or the other, it has been shown in the last few years that this assumption is an oversi...

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Bibliographic Details
Published inComputer Aided Systems Theory - EUROCAST 2013 pp. 364 - 371
Main Authors Scheibenpflug, Andreas, Wagner, Stefan
Format Book Chapter
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg 2013
SeriesLecture Notes in Computer Science
Subjects
Crossover Operator
Genetic Algorithm
Mutation Operator
Problem Instance
Travel Salesman Problem
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Summary:Intensification and diversification are two driving forces in genetic algorithms and are frequently the subject of research. While it seemed for decades that a genetic operator can be classified as either the one or the other, it has been shown in the last few years that this assumption is an oversimplified view and most operators exhibit both, diversification and intensification, to some degree. Most papers in this field focus on a certain operator or algorithm configuration as theoretical and generalizable foundations are hard to obtain. In this paper we therefore use a wide range of different configurations and behavior measurements to study the intensification and diversification behavior of genetic algorithms and their operators.
ISBN:364253855X
9783642538551
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-642-53856-8_46