Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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On the Comparison of Particle Swarm Optimization Algorithm Performance using Beta Probability Distribution

베타 확률분포를 이용한 입자 떼 최적화 알고리즘의 성능 비교

  • Lee, ByungSeok (School of Electrical and Computer Engineering, University of Seoul) ;
  • Lee, Joon Hwa (School of Electrical and Computer Engineering, University of Seoul) ;
  • Heo, Moon-Beom (Satellite Navigation Team, Korea Aerospace Research Institute)
  • 이병석 (서울시립대학교 전자전기컴퓨터공학부 및 한국항공우주연구원 위성항법팀) ;
  • 이준화 (서울시립대학교 전자전기컴퓨터공학부) ;
  • 허문범 (한국항공우주연구원 위성항법팀)
  • Received : 2013.12.25
  • Accepted : 2014.06.02
  • Published : 2014.08.01
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Abstract

This paper deals with the performance comparison of a PSO algorithm inspired in the process of simulating the behavior pattern of the organisms. The PSO algorithm finds the optimal solution (fitness value) of the objective function based on a stochastic process. Generally, the stochastic process, a random function, is used with the expression related to the velocity included in the PSO algorithm. In this case, the random function of the normal distribution (Gaussian) or uniform distribution are mainly used as the random function in a PSO algorithm. However, in this paper, because the probability distribution which is various with 2 shape parameters can be expressed, the performance comparison of a PSO algorithm using the beta probability distribution function, that is a random function which has a high degree of freedom, is introduced. For performance comparison, 3 functions (Rastrigin, Rosenbrock, Schwefel) were selected among the benchmark Set. And the convergence property was compared and analyzed using PSO-FIW to find the optimal solution.

Keywords

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