A Hybrid Constrained Optimization Approach Coupling PSO and Adaptive Constraint-Handling Technique

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Abstract: In this paper, we present a novel hybrid approach combining particle swarm optimization (PSO) and adaptive constraint-handling technique (ACT) for solving constrained numerical and engineering optimization problems. The proposed hybrid approach simultaneously adopts particle swarm optimizer and hybrid mutation operators to generate the offspring population. Additionally, the adaptive constraint-handling technique includes three main situations. In each situation, a constraint-handling mechanism is designed based on current population state. Our algorithm is validated using 15 well-known constrained numerical and engineering optimization problems reported in the literature. The experimental results demonstrate that the proposed method shows better performance in comparison to the state-of-the-art algorithms.

WSEAS Transactions on Circuits and Systems, ISSN / E-ISSN: 1109-2734 / 2224-266X, Volume 15, 2016, Art. #8

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Wen Long, Shaohong Cai, Jianjun Jiao, Wenzhuan Zhang, "A Hybrid Constrained Optimization Approach Coupling PSO and Adaptive Constraint-Handling Technique ," WSEAS Transactions on Circuits and Systems, vol. 15, pp. 55-63, 2016, DOI:
Wen Long, Shaohong Cai, Jianjun Jiao, Wenzhuan Zhang. A Hybrid Constrained Optimization Approach Coupling PSO and Adaptive Constraint-Handling Technique . WSEAS Transactions on Circuits and Systems. 2016;15:55-63.
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