A dynamically switched crossover for genetic algorithms

Liang Ming*, Yiu Ming CHEUNG, Yu Ping Wang

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

The traditional crossover operator performs the constant crossover between two parents without considering their homogeneity. Actually, the more homogeneous the parents are, the more disruptive the crossover should be. In this paper, a self-adaptive mechanism named Adaptive Recombination with Three Sub-populations (ARTS) is therefore presented to control the crossover operator of a genetic algorithm. The ARTS allows the crossover to be dynamically switched among two-point crossover (i.e., the least disruptive crossover), uniform crossover with probability 0.2, and uniform crossover with probability 0.5 (i.e., the most disruptive crossover). The experiments have shown the promising results.

Original languageEnglish
Title of host publicationProceedings of 2004 International Conference on Machine Learning and Cybernetics
Pages3254-3257
Number of pages4
Publication statusPublished - 2004
EventProceedings of 2004 International Conference on Machine Learning and Cybernetics - Shanghai, China
Duration: 26 Aug 200429 Aug 2004

Publication series

NameProceedings of 2004 International Conference on Machine Learning and Cybernetics
Volume5

Conference

ConferenceProceedings of 2004 International Conference on Machine Learning and Cybernetics
Country/TerritoryChina
CityShanghai
Period26/08/0429/08/04

Scopus Subject Areas

  • Engineering(all)

User-Defined Keywords

  • Adaptive recombination with three sub-populations (ARTS)
  • Crossover operator
  • Dynamic switch
  • Genetic algorithm

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