A Constrained Particle Swarm Optimization Algorithm with Oracle Penalty Method

Abstract:

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To solve constrained optimization problems, an Oracle penalty method-based comprehensive learning particle swarm optimization (OBCLPSO) algorithm was proposed. First, original Oracle penalty was modified. Secondly, the modified Oracle penalty method was combine with comprehensive learning particle swarm optimization algorithm. Finally, experimental results and comparisons were given to demonstrate the optimization performances of OBCLPSO. The results show that the proposed algorithm is a very competitive approach for constrained optimization problems.

Info:

Periodical:

Edited by:

Yun-Hae Kim and Prasad Yarlagadda

Pages:

1519-1523

DOI:

10.4028/www.scientific.net/AMM.303-306.1519

Citation:

M. G. Dong et al., "A Constrained Particle Swarm Optimization Algorithm with Oracle Penalty Method", Applied Mechanics and Materials, Vols. 303-306, pp. 1519-1523, 2013

Online since:

February 2013

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Price:

$35.00

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