Proceedings of the Korean Institute of Intelligent Systems Conference (한국지능시스템학회:학술대회논문집)

Korean Institute of Intelligent Systems (한국지능시스템학회)
권호 표지

Optimization of Crossover and Mutation Rate Using PGA-Based meta-GA

병렬 유전 알고리즘 기반 meta-유전 알고리즘을 이용한 교차율과 돌연변이율의 최적화

  • 김문환 (연세대학교 전기전자공학과) ;
  • 박진배 (연세대학교 전기전자공학과) ;
  • 이연우 (군산대학교 전자정보공학부) ;
  • 주영훈 (군산대학교 전자정보공학부)
  • Published : 2002.12.01

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Abstract

In this paper we propose parallel GA to optimize mutation rate and crossover rate using server-client model. The performance of GA depend on the good choice of crossover and mutation rates. Although many researcher has been study about the good choice, it is still unsolved problem. proposed GA optimize crossover and mutation rates trough evolving subpopulation. In virtue of the server-client model, these parameters can be evolved rapidly with relatively low-grade

Keywords