Adaptively Species-Migration-Based Multimodal Particle Swarm Optimization

被引：0

作者：

Liu, Yu ^{[1
,2
]}

Lv, Mingwei ^{[1
,2
]}

Li, Wentao ^{[1
,2
]}

Fang, Jing ^{[1
,2
]}

Zhao, Lei ^{[1
,2
]}

机构：

[1] School of Software, Dalian University of Technology, Dalian 116621, China

[2] Institute of IT Service Engineering and Management, Dalian University of Technology, Dalian 116621, China

来源：

Journal of Computational Information Systems | 2011年 / 7卷 / 07期

关键词：

Information systems;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Niching technique plays an important role in multimodal function optimization. This paper introduces species migration and removes duplicate species into niching algorithms and proposes Adaptively Species-Migration-Based Multimodal Particle Swarm Optimization (SMPSO). The proposed algorithm doesn't rely on any prespecified niching parameter. Experiments show that SMPSO has higher success rate and needs lower computation cost than ANPSO in handling most of standard multimodal functions. Copyright © 2011 Binary Information Press.

引用

页码：2379 / 2386