Modified Binary Particle Swarm Optimization using Genotype-Phenotype Concept (Version 2)

유전자형-표현형 개념을 적용한 수정된 이진 입자군집최적화 (버전 2)

  • 임승균 (목원대학교 정보통신융합공학부) ;
  • 이상욱 (목원대학교 정보통신융합공학부)
  • Received : 2014.09.11
  • Accepted : 2014.10.20
  • Published : 2014.11.28


In this paper, we introduce a second version of modified binary particle swarm optimization using a concept of genotype-phenotype in genetic algorithms. Particle swarm optimization uses an information of difference between a position of the best solution and one's own position in the process of searching optimum. To obtain this difference of positions, the first version of modified binary particle swarm optimization uses a phenotype but the proposed second version uses a genotype. We can represent the solution space in large search space by using a genotype which provides continuous whole space as search space compared to a phenotype which provides only binary information. Experimental results in 10 De Jong benchmark function show that the second version outperforms the first version in six functions which has a broad search space and many local optima.


Binary Particle Swarm Optimization;Genotype-phenotype


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