Particle Swarm Optimizer Networks with Stochastic Connection for Improvement of Diversity Search Ability to Solve Multimodal Optimization Problems

被引：2

作者：

Sasaki, Tomoyuki ^{[1
]}

Nakano, Hidehiro ^{[2
]}

Miyauchi, Arata ^{[1
]}

Taguchi, Akira ^{[1
]}

机构：

[1] Tokyo City Univ, Tokyo 1588557, Japan

[2] Tokyo City Univ, Dept Comp Sci, Tokyo 1588557, Japan

来源：

IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES | 2017年 / E100A卷 / 04期

关键词：

metaheuristic methods; particle swarm optimizer networks; network topology; stochastic connection;

D O I：

10.1587/transfun.E100.A.996

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Particle swarm optimizer network (PSON) is one of the multi-swarm PSOs. In PSON, a population is divided into multiple subPSOs, each of which searches a solution space independently. Although PSON has a good solving performance, it may be trapped into a local optimum solution. In this paper, we introduce into PSON a dynamic stochastic network topology called "PSON with stochastic connection" (PSON-SC). In PSON-SC, each sub-PSO can be connected to the global best (gbest) information memory and refer to gbest stochastically. We show clearly herein that the diversity of PSON-SC is higher than that of PSON, while confirming the effectiveness of PSON-SC by many numerical simulations.

引用

页码：996 / 1007

页数：12

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