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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Bibliographic Details
Published in:Applied Mechanics and Materials Vol. 303-306; pp. 1519 - 1523
Main Authors: Dong, Ming Gang, Cheng, Xiao Hui, Niu, Qin Zhou
Format: Journal Article
Language:English
Published: Zurich Trans Tech Publications Ltd 01.02.2013
Subjects:
Constrained Optimization Problems
Constraints Handling
Particle Swarm Optimization (PSO)
Oracle Penalty Method
ISBN:3037856521, 9783037856529
ISSN:1660-9336, 1662-7482, 1662-7482
Online Access:Get full text
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Summary: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.
Bibliography: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