A novel particle swarm optimizer with time-delay
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
| Original language | English |
|---|---|
| Pages (from-to) | 789-793 |
| Journal / Publication | Applied Mathematics and Computation |
| Volume | 186 |
| Issue number | 1 |
| Publication status | Published - 1 Mar 2007 |
Link(s)
Abstract
Particle swarm optimization (PSO) is a relatively new population-based heuristic optimization technique. It has been widely applied to optimization problems for simplicity and capability of finding fairly good solutions rapidly. However, it may be trapped in local optima and fails to converge to global optimum. In this paper, the concept of time-delay is introduced into PSO to control the process of information diffusion and keep the particle diversity. Four time-delay schemes are proposed then. Experimental results verify their superiority both in robustness and efficiency. Conclusions are drawn in the end. © 2006 Elsevier Inc. All rights reserved.
Research Area(s)
- Diversity, Particle swarm optimization, Time-delay
Citation Format(s)
A novel particle swarm optimizer with time-delay. / Xiang, Tao; Wong, Kwok-wo; Liao, Xiaofeng.
In: Applied Mathematics and Computation, Vol. 186, No. 1, 01.03.2007, p. 789-793.Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
