An Improved Attractive and Repulsive Particle Swarm Optimization for Nonconvex Economic Dispatch Problems

被引：8
|
作者：
Baek, Min-Kyu [1 ]
Park, Jong-Bae [1 ]
Lee, Kwang Y. [2 ]
机构：
[1] Konkuk Univ, Elect Engn Dept, Seoul, South Korea
[2] Baylor Univ, Elect & Comp Engn, Waco, TX 76798 USA
来源：
IFAC PAPERSONLINE | 2016年 / 49卷 / 27期
关键词：
PSO; ARPSO; non-convex optimization; economic dispatch; heuristic algorithm;
D O I：
10.1016/j.ifacol.2016.10.705
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper presents an improved attractive and repulsive particle swarm optimization (ARPSO) algorithm for nonconvex economic dispatch problem. The ARPSO algorithm enhances the exploration and exploitation behaviors of a particle by observing a diversity factor. This paper develops an improved ARPSO by introducing a penalty factor that forces each particle to repulse from the global worst particle. The advantage of the improved ARPSO is demonstrated numerically in comparison with the basic PSO and other variation of ARPSO. (c) 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
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页码：284 / 289
页数：6
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