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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)

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Abstract

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
Depositing User: Mark Wheadon
Date Deposited: 24 Nov 2008 18:02 UTC
Last Modified: 16 Feb 2021 12:25 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/14249 (The current URI for this page, for reference purposes)
Freitas, Alex A.: https://orcid.org/0000-0001-9825-4700
Johnson, Colin G.: https://orcid.org/0000-0002-9236-6581
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