Novel global harmony search algorithm for unconstrained problems

被引：123

作者：

Zou, Dexuan ^{[1
]}

Gao, Liqun ^{[1
]}

Wu, Jianhua ^{[1
]}

Li, Steven ^{[2
]}

机构：

[1] Northeastern Univ, Sch Informat Sci & Engn, Shenyang 110004, Liaoning, Peoples R China

[2] Univ S Australia, Div Business, Adelaide, SA 5001, Australia

来源：

NEUROCOMPUTING | 2010年 / 73卷 / 16-18期

基金：

美国国家科学基金会;

关键词：

Novel global harmony search algorithm; Position updating; Genetic mutation; Convergence; Stability; Harmony search algorithm; OPTIMIZATION; COLONY;

D O I：

10.1016/j.neucom.2010.07.010

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, we use a recently proposed algorithm-novel global harmony search (NGHS) algorithm to solve unconstrained problems. The NGHS algorithm includes two important operations: position updating and genetic mutation with a low probability. The former can enhance the convergence of the NGHS, and the latter can effectively prevent the NGHS from being trapped into the local optimum. Based on a large number of experiments, the NGHS has demonstrated stronger convergence and stability than original harmony search (HS) algorithm and its two improved algorithms (IHS and SGHS). (C) 2010 Elsevier B.V. All rights reserved.

引用

页码：3308 / 3318

页数：11

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