文章基本信息

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 ; 宮内新等
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