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Estimation of particle swarm distribution algorithms: Bringing together the strengths of PSO and EDAs

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Abstract
This paper presents a framework of estimation of particle swarm distribution algorithms (EPSDAs). The aim lies in effectively combining particle swarm optimization (PSO) with estimation of distribution algorithms (EDAs) without losing on their unique features. To exhibit its practicability, an extended compact particle swarm optimization (EcPSO) is developed along the lines of the suggested framework. Empirical results have adduced grounds for its effectiveness.
Author(s)
Hyun-Tae KimAhn, Chang Wook
Issued Date
2009-07
Type
Conference Paper
DOI
10.1145/1569901.1570178
URI
https://scholar.gist.ac.kr/handle/local/25582
Publisher
ACM SIGEVO
Citation
11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009, pp.1817 - 1818
Conference Place
CN
Appears in Collections:
Department of AI Convergence > 2. Conference Papers
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