Iqbal, M. and de Oca, M.A.M. (2006) An Estimation of Distribution Particle Swarm Optimization Algorithm. In: Dorigo, M., ed. Ant Colony Optimization and Swarm Intelligence. Lecture Notes in Computer Science, 4150 . Springer Verlag, Berlin, Germany, pp. 72-83. ISBN 978-3-540-38482-3.
In this paper we present an estimation of distribution par-ticle swarm optimization algorithm that borrows ideas from recent de-velopments in ant colony optimization. In the classical particle swarm optimization algorithm, particles exploit their individual memory to ex-plore the search space. However, the swarm as a whole has no means to exploit its collective memory (represented by the array of pbests) to guide its search. This causes a re-exploration of already known bad regions of the search space, wasting costly function evaluations. In our approach, we use the swarms collective memory to estimate the distribu-tion of promising regions in the search space and probabilistically guide the particles movement towards them. Our experiments show that this approach is able to find similar or better solutions than the standard particle swarm optimizer with fewer function evaluations.
|Item Type:||Book section|
|Uncontrolled keywords:||Particle Swarm Optimization, Estimation of Distribution|
|Subjects:||Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,|
|Divisions:||Faculties > Science Technology and Medical Studies > School of Computing > Applied and Interdisciplinary Informatics Group|
|Depositing User:||Mark Wheadon|
|Date Deposited:||24 Nov 2008 18:03|
|Last Modified:||27 Jun 2012 09:53|
|Resource URI:||http://kar.kent.ac.uk/id/eprint/14436 (The current URI for this page, for reference purposes)|
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