Skip to main content

Varying the Topology and Probability of Re-Initialization in Particle Swarm Optimization

Iqbal, Musaddar, Freitas, Alex A., Johnson, Colin G. (2005) Varying the Topology and Probability of Re-Initialization in Particle Swarm Optimization. In: Talbi, El-Ghazali, ed. Evolution Artificielle 2005. . (KAR id:14249)

Language: English
Click to download this file (341kB) Preview
[thumbnail of Varmud.pdf]
This file may not be suitable for users of assistive technology.
Request an accessible format


This paper introduces two new versions of dissipative particle swarm optimization. Both of these use a new time-dependent strategy for randomly re-initializing the positions of the particles. In addition, one variation also uses a novel dynamic neighbourhood topology based on small world networks. We present results from applying these algorithms to two well-known function optimization problems. Both algorithms perform considerably better than both standard PSO and the original dissipative PSO algorithms. In particular one version performs significantly better on high-dimensional problems that are inaccessible to traditional methods.

Item Type: Conference or workshop item (UNSPECIFIED)
Uncontrolled keywords: PSO; swarm intelligence; small-world theory
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Funders: University of Lille (
Depositing User: Mark Wheadon
Date Deposited: 24 Nov 2008 18:02 UTC
Last Modified: 12 Jul 2022 10:39 UTC
Resource URI: (The current URI for this page, for reference purposes)
Freitas, Alex A.:
Johnson, Colin G.:
  • Depositors only (login required):

Total unique views for this document in KAR since July 2020. For more details click on the image.