A Constrained Particle Swarm Optimization Algorithm with Oracle Penalty Method

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 s...

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Veröffentlicht in:Applied Mechanics and Materials Jg. 303-306; S. 1519 - 1523
Hauptverfasser: Dong, Ming Gang, Cheng, Xiao Hui, Niu, Qin Zhou
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Zurich Trans Tech Publications Ltd 01.02.2013
Schlagworte:
Constrained Optimization Problems
Constraints Handling
Particle Swarm Optimization (PSO)
Oracle Penalty Method
ISBN:3037856521, 9783037856529
ISSN:1660-9336, 1662-7482, 1662-7482
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Zusammenfassung: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.
Bibliographie:Selected papers from the 2012 International Conference on Sensors, Measurement and Intelligent Materials (ICSMIM 2012), December 26-27, 2012, Guilin, China
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ISBN:3037856521
9783037856529
ISSN:1660-9336
1662-7482
1662-7482
DOI:10.4028/www.scientific.net/AMM.303-306.1519