A framework for studying the effects of dynamic crossover, mutation, and population sizing in genetic algorithms

Michael A. Lee, Hideyuki Takagi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

We introduce a framework for controlling genetic algorithms and use it to study the effect of dynamically modulating genetic algorithm control . parameters on search behavior. Our framework includes techniques that can automatically design control strategies for genetic algorithms according to a given search performance metric. Many of the automatically designed strategies exhibit an exponentially decreasing mutation rate behavior. We present experimental results indicating that exponentially decreasing the mutation rate over time contributes more towards an increase on online and offiine search performance than populations size or crossover rate modulation.

Original languageEnglish
Title of host publicationAdvances in Fuzzy Logic, Neural Networks and Genetic Algorithms - IEEE/Nagoya-University World Wisepersons Workshop, 1994, Selected Papers
EditorsTakeshi Furuhashi
PublisherSpringer Verlag
Pages111-126
Number of pages16
ISBN (Print)9783540606079
DOIs
Publication statusPublished - Jan 1 1995
Event3rd World Wisepersons Workshop on Fuzzy Logic and Neural Networks/Genetic Algorithms, WWW 1994 - Nagoya, Japan
Duration: Aug 9 1994Aug 10 1994

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1011
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other3rd World Wisepersons Workshop on Fuzzy Logic and Neural Networks/Genetic Algorithms, WWW 1994
CountryJapan
CityNagoya
Period8/9/948/10/94

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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    Lee, M. A., & Takagi, H. (1995). A framework for studying the effects of dynamic crossover, mutation, and population sizing in genetic algorithms. In T. Furuhashi (Ed.), Advances in Fuzzy Logic, Neural Networks and Genetic Algorithms - IEEE/Nagoya-University World Wisepersons Workshop, 1994, Selected Papers (pp. 111-126). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1011). Springer Verlag. https://doi.org/10.1007/3-540-60607-6_9