COMPARISON OF PARTICLE SWARM AND EVOLUTIONARY PROGRAMMING AS THE GLOBAL CONFORMATION OPTIMIZER OF CLUSTERS

Masao Iwamatsu ()
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Masao Iwamatsu: Department of Physics, General Education Center, Musashi Institute of Technology, Setagaya-ku, Tokyo 158-8557, Japan

International Journal of Modern Physics C (IJMPC), 2005, vol. 16, issue 04, 591-606

Abstract: The particle swarm optimization (PSO) algorithm and two variants of the evolutionary programming (EP) are applied to the several function optimization problems and the conformation optimization of atomic clusters to check the performance of these algorithms as a general-purpose optimizer. It was found that the PSO is superior to the EP though the PSO is not equipped with the mechanism of self-adaptation of search strategies of the EP. The PSO cannot find the global minimum for the atomic cluster but can find it for similar multi-modal benchmark functions of the same size. The size of the cluster which can be handled by the PSO and the EP is limited, and is similar to the one amenable to the popular simulated annealing. The result for benchmark functions only serves as an indication of the performance of the algorithm.

Keywords: Particle swarm; evolutionary programming; conformation optimization (search for similar items in EconPapers)
Date: 2005
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DOI: 10.1142/S0129183105007340

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