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  • 标题:区分線形系粒子群最適化法における解探索性能の解析
  • 本地全文:下载
  • 作者:佐々木 智志 ; 中野 秀洋 ; 宮内 新
  • 期刊名称:進化計算学会論文誌
  • 电子版ISSN:2185-7385
  • 出版年度:2017
  • 卷号:8
  • 期号:1
  • 页码:1-10
  • DOI:10.11394/tjpnsec.8.1
  • 出版社:The Japanese Society for Evolutionary Computation
  • 摘要:Herein, we propose a piecewise-linear particle swarm optimizer (PPSO).PPSO is one of the deterministic PSO, which has two search dynamics, a convergence mode and a divergence mode.Solving performances of PPSO are significantly affected by connective coefficient γ.We investigate relations between solving performances and the connective coefficient, and reveal a method of setting the connective coefficient according to the structure of a solution space.We further compare the solving performances of PPSO with those of other deterministic PSO methods and classic PSO in the numerical experiments.
  • 关键词:metaheuristics ; particle swarm optimization ; piecewise-linear system ; piecewise-linear particle swarm optimizer
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