Dynamic multi-swarm particle swarm optimizer with harmony search

被引：100
|
作者：
Zhao, S. -Z. [1 ]
Suganthan, P. N. [1 ]
Pan, Quan-Ke [2 ]
Tasgetiren, M. Fatih [3 ]
机构：
[1] Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore 639798, Singapore
[2] Liaocheng Univ, Coll Comp Sci, Liaocheng 252059, Peoples R China
[3] Yasar Univ, Dept Ind Engn, Izmir, Turkey
来源：
EXPERT SYSTEMS WITH APPLICATIONS | 2011年 / 38卷 / 04期
关键词：
Particle swarm optimizer; Dynamic multi-swarm particle swarm optimizer; Harmony search; Dynamic sub-swarms; Numerical optimization; Multimodal optimization;
D O I：
10.1016/j.eswa.2010.09.032
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, the dynamic multi-swarm particle swarm optimizer (DMS-PSO) is improved by hybridizing it with the harmony search (HS) algorithm and the resulting algorithm is abbreviated as DMS-PSO-HS. We present a novel approach to merge the HS algorithm into each sub-swarm of the DMS-PSO. Combining the exploration capabilities of the DMS-PSO and the stochastic exploitation of the HS, the DMS-PSO-HS is developed. The whole DMS-PSO population is divided into a large number of small and dynamic sub-swarms which are also individual HS populations. These sub-swarms are regrouped frequently and information is exchanged among the particles in the whole swarm. The DMS-PSO-HS demonstrates improved on multimodal and composition test problems when compared with the DMS-PSO and the HS. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码：3735 / 3742
页数：8
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