A Modified Algorithm for Particle Swarm Optimization with Constriction Coefficient | ||||
| IJCI. International Journal of Computers and Information | ||||
| Article 2, Volume 2, Issue 1, June 2009, Page 17-29 PDF (163.28 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/ijci.2009.33935 | ||||
 View on SCiNiTO | ||||
| Author | ||||
| Mahmoud M. El-Sherbiny | ||||
| Operations Research Dept, Institute of Statistical Studies and Research (ISSR), Cairo University, Egypt. | ||||
| Abstract | ||||
| This paper introduces a modified algorithm to partical swarm based optimization that significantly reduces the number of iterations required to reach good solutions and discusses the results of experimentally comparing its performance with the performance of several variants of the standard particle swarm optimizer. The variants of the modified algorithm and the most common variants of the particle swarm optimizers are tested using a set of multimodal functions commonly used as benchmark optimization problems in evolutionary computation. Results indicate that the algorithm is highly competitive and can be considered as aviable alternative to solve the optimization problems. | ||||
| Keywords | ||||
| Particle Swarm Optimization; Convergence; Evolutionary computation; constriction coefficient | ||||
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