An Effective Particle Swarm Optimization for Global Optimization

被引：0

作者：

Eslami, Mahdiyeh ^{[1
]}

Shareef, Hussain ^{[1
]}

Khajehzadeh, Mohammad ^{[2
]}

Mohamed, Azah ^{[1
]}

机构：

[1] Natl Univ Malaysia, Elect Elect & Syst Engn Dept, Selangor, Malaysia

[2] Islamic Azad Univ, Anar Branch, Dept Civil Engn, Anar, Iran

来源：

COMPUTATIONAL INTELLIGENCE AND INTELLIGENT SYSTEMS | 2012年 / 316卷

关键词：

Particle Swarm Optimization; Chaotic Sequence; Nonlinear Acceleration Coefficient; Global Optimization; DESIGN;

D O I：

暂无

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, a novel chaotic particle swarm optimization with nonlinear time varying acceleration coefficient is introduced. The proposed modified particle swarm optimization algorithm (MPSO) greatly elevates global and local search abilities and overcomes the premature convergence of the original algorithm. This study aims to investigate the performance of the new algorithm, as an effective global optimization method, on a suite of some well-known benchmark functions and provides comparisons with the standard version of the algorithm. The simulated results illustrate that the proposed MPSO has the potential to converge faster, while improving the quality of solution. Experimental results confirm superior performance of the new method compared with standard PSO.

引用

页码：267 / +

页数：3

共 19 条

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Eslami, Mahdiyeh ;

Shareef, Hussain ;

Mohamed, Azah .

JOURNAL OF CENTRAL SOUTH UNIVERSITY OF TECHNOLOGY, 2011, 18 (05) :1579-1588

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