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A Modified Particle Swarm Optimization Algorithm : Information Diffusion PSO

새로운 위상 기반의 Particle Swarm Optimization 알고리즘 : 정보파급 PSO

  • Park, Jun-Hyuk (Institute of Information Technology, Inc.) ;
  • Kim, Byung-In (Department of Industrial and Management Engineering, Pohang University of Science and Technology (POSTECH))
  • 박준혁 (미국 Institute of Information Technology사) ;
  • 김병인 (포항공과대학교 산업경영공학과)
  • Received : 2011.05.05
  • Accepted : 2011.06.07
  • Published : 2011.09.01

Abstract

This paper proposes a modified version of Particle Swarm Optimization (PSO) called Information Diffusion PSO (ID-PSO). In PSO algorithms, premature convergence of particles could be prevented by defining proper population topology. In this paper, we propose a variant of PSO algorithm using a new population topology. We draw inspiration from the theory of information diffusion which models the transmission of information or a rumor as one-to-one interactions between people. In ID-PSO, a particle interacts with only one particle at each iteration and they share their personal best solutions and recognized best solutions. Each particle recognizes the best solution that it has experienced or has learned from another particle as the recognized best. Computational experiments on the benchmark functions show the effectiveness of the proposed algorithm compared with the existing methods which use different population topologies.

Keywords

References

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