Enhanced leader PSO (ELPSO): A new PSO variant for solving global optimisation problems

被引:197
作者
Jordehi, A. Rezaee [1 ]
机构
[1] Univ Putra Malaysia, Dept Elect Engn, Upm Serdang 43400, Selangor, Malaysia
关键词
Particle swarm optimisation; Global optimisation; Heuristics; PARTICLE SWARM OPTIMIZATION; ALGORITHM; OPPOSITION; PLACEMENT;
D O I
10.1016/j.asoc.2014.10.026
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Particle swarm optimisation (PSO) is a well-established optimisation algorithm inspired from flocking behaviour of birds. The big problem in PSO is that it suffers from premature convergence, that is, in complex optimisation problems, it may easily get trapped in local optima. In this paper, a new PSO variant, named as enhanced leader PSO (ELPSO), is proposed for mitigating premature convergence problem. ELPSO is mainly based on a five-staged successive mutation strategy which is applied to swarm leader at each iteration. The experimental results confirm that in all terms of accuracy, scalability and convergence rate, ELPSO performs well. (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码:401 / 417
页数:17
相关论文
共 43 条
[31]   Opposition versus randomness in soft computing techniques [J].
Rahnamayan, Shahryar ;
Tizhoosh, Hamid R. ;
Salama, Magdy M. A. .
APPLIED SOFT COMPUTING, 2008, 8 (02) :906-918
[32]   Opposition-based differential evolution [J].
Rahnamayan, Shahryar ;
Tizhoosh, Hamid R. ;
Salama, Magdy M. A. .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2008, 12 (01) :64-79
[33]   GSA: A Gravitational Search Algorithm [J].
Rashedi, Esmat ;
Nezamabadi-Pour, Hossein ;
Saryazdi, Saeid .
INFORMATION SCIENCES, 2009, 179 (13) :2232-2248
[34]  
Rezaee Jordehi A., INT J ELECT POWER EN, V64, P771
[35]   Cellular particle swarm optimization [J].
Shi, Yang ;
Liu, Hongcheng ;
Gao, Liang ;
Zhang, Guohui .
INFORMATION SCIENCES, 2011, 181 (20) :4460-4493
[36]   A modified particle swarm optimizer [J].
Shi, YH ;
Eberhart, R .
1998 IEEE INTERNATIONAL CONFERENCE ON EVOLUTIONARY COMPUTATION - PROCEEDINGS, 1998, :69-73
[37]  
Shi YH, 2011, INT J SWARM INTELL R, V2, P35, DOI [10.4018/ijsir.2011100103, 10.4018/jsir.2011100103]
[38]   Nonconvex resource control and lifetime optimization in wireless video sensor networks based on chaotic particle swarm optimization [J].
Tang, Meiqin ;
Xin, Yalin ;
Li, Jing ;
Zhai, Jingang .
APPLIED SOFT COMPUTING, 2013, 13 (07) :3273-3284
[39]  
Tvrdík J, 2013, 2013 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), P1651
[40]   Diversity enhanced particle swarm optimization with neighborhood search [J].
Wang, Hui ;
Sun, Hui ;
Li, Changhe ;
Rahnamayan, Shahryar ;
Pan, Jeng-shyang .
INFORMATION SCIENCES, 2013, 223 :119-135