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| Fuzzy Particle Swarm Optimization for Constrained Optimization Problems |
| Wei Jing-xuan①; Wang Yu-ping② |
| ①Department of Mathematics Science, Xidian University, Xi’an 710071, China;②School of Computer Science and Technology, Xidian University, Xi’an 710071, China |
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Abstract A fuzzy particle swarm optimization is proposed for solving complex constrained optimization problems. Firstly, a new perturbation operator is designed, and the concepts of fuzzy personal best value and fuzzy global best value are given based on the new operator. Particle updating equations are revised based upon the two new concepts to discourage the premature convergence. Secondly, a new comparison strategy is proposed based on the new concept of infeasible threshold value. It can preserve some infeasible solutions with high quality. Finally, the convergence of this algorithm is proved. The simulation results show that the proposed algorithm is effective, especially for the problems with high dimensions.
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Received: 08 May 2007
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2008, Vol. 30 
