A New Selection Algorithms for Distributed Evolutionary Algorithms

  • Oh, Sang-Keon (Department of Electrical Engineering and Computer Science, Korea Advance Institute of Science and Technology) ;
  • Kim, Cheol-Taek (Department of Electrical Engineering and Computer Science, Korea Advance Institute of Science and Technology) ;
  • Lee, Ju-Jang (Department of Electrical Engineering and Computer Science, Korea Advance Institute of Science and Technology)
  • 발행 : 2000.10.01

초록

Parallel genetic algorithms are particularly easy to implement and promise substantial gains in performance. Its basic idea is to keep several subpopulations that are processed by genetic algorithms. Furthermore, a migration mechanism produces a chromosome exchange between subpopulation. In this paper, a new selection method based on non-linear fitness assignment presented. The use of proposed ranking selection permits higher local exploitation search, where the diversity of populations is structure. Experimental results show that the relation between local-global search balance and the probabilities of reaching a desired solution.

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