Balanced fuzzy particle swarm optimization

被引：14

作者：

Robati, Amir ^{[1
,2
]}

Barani, Gholam Abbas ^{[3
]}

Pour, Hossein Nezam Abadi ^{[4
]}

Fadaee, Mohammad Javad ^{[3
]}

Anaraki, Javad Rahimi Pour ^{[5
]}

机构：

[1] Shahid Bahonar Univ, Dept Civil Engn, Kerman 7613633768, Iran

[2] Azad Univ Kerman Branch, Dept Civil Engn, Kerman, Iran

[3] Shahid Bahonar Univ Kerman, Coll Engn, Dept Civil Engn, Kerman, Iran

[4] Shahid Bahonar Univ Kerman, Coll Engn, Dept Elect Engn, Kerman, Iran

[5] Shahid Bahonar Univ, Dept Comp Engn, Kerman 7613633768, Iran

来源：

APPLIED MATHEMATICAL MODELLING | 2012年 / 36卷 / 05期

关键词：

Balanced fuzzy; Discrete optimization; Particle swarm optimization; Membership function; ALGORITHM;

D O I：

10.1016/j.apm.2011.08.006

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

In the present study an extension of particle swarm optimization (PSO) algorithm which is in conformity with actual nature is introduced for solving combinatorial optimization problems. Development of this algorithm is essentially based on balanced fuzzy sets theory. The classical fuzzy sets theory cannot distinguish differences between positive and negative information of membership functions, while in the new method both kinds of information "positive and negative" about membership function are equally important. The balanced fuzzy particle swarm optimization algorithm is used for fundamental optimization problem entitled traveling salesman problem (TSP). For convergence inspecting of new algorithm, method was used for TSP problems. Convergence curves were represented fast convergence in restricted and low iterations for balanced fuzzy particle swarm optimization algorithm (BF-PSO) comparison with fuzzy particle swarm optimization algorithm (F-PSO). (C) 2011 Elsevier Inc. All rights reserved.

引用

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页码：2169 / 2177

页数：9

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