Particle Swarm Optimization - A Survey

被引：78
作者：
Kameyama, Keisuke [1 ]
机构：
[1] Univ Tsukuba, Grad Sch Syst & Informat Engn, Tsukuba, Ibaraki 3058573, Japan
来源：
IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS | 2009年 / E92D卷 / 07期
关键词：
particle swarm optimization; swarm intelligence; GLOBAL OPTIMIZATION; CONVERGENCE; STABILITY;
D O I：
10.1587/transinf.E92.D.1354
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Particle Swarm Optimization (PSO) is a search method which utilizes a set of agents that move through the search space to find the global minimum of an objective function. The trajectory of each particle is determined by a simple rule incorporating the current particle velocity and exploration histories of the particle and its neighbors. Since its introduction by Kennedy and Eberhart in 1995, PSO has attracted many researchers due to its search efficiency even for a high dimensional objective function with multiple local optima. The dynamics of PSO search has been investigated and numerous variants for improvements have been proposed. This paper reviews the progress of PSO research so far, and the recent achievements for application to large-scale optimization problems.
引用
收藏
页码：1354 / 1361
页数：8
相关论文
共 39 条
[1]  
Al-kazemi B, 2002, IEEE C EVOL COMPUTAT, P489, DOI 10.1109/CEC.2002.1006283
[2]   Using selection to improve particle swarm optimization [J].
Angeline, PJ .
1998 IEEE INTERNATIONAL CONFERENCE ON EVOLUTIONARY COMPUTATION - PROCEEDINGS, 1998, :84-89
[3]  
Binkley KJ, 2005, 2005 IEEE SWARM INTELLIGENCE SYMPOSIUM, P45
[4]   Multiswarms, exclusion, and anti-convergence in dynamic environments [J].
Blackwell, Tim ;
Branke, Juergen .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2006, 10 (04) :459-472
[5]   The particle swarm - Explosion, stability, and convergence in a multidimensional complex space [J].
Clerc, M ;
Kennedy, J .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2002, 6 (01) :58-73
[6]  
Coello CAC, 2004, IEEE T EVOLUT COMPUT, V8, P256, DOI [10.1109/TEVC.2004.826067, 10.1109/tevc.2004.826067]
[7]  
De Jong K. A., 1975, Ph.D. Thesis
[8]  
Eberhart R C., 2001, Swarm Intelligence, V1
[9]   Particle swarm optimization with Gaussian mutation [J].
Higashi, N ;
Iba, H .
PROCEEDINGS OF THE 2003 IEEE SWARM INTELLIGENCE SYMPOSIUM (SIS 03), 2003, :72-79
[10]  
HU X, 2001, IEEE SWARM INT S, P193
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