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A Constraint Consensus Vector-based PSO Algorithm for Solving Engineering Optimization Problems

陶少辉  Tianhao Zhang  Shuguang Xiang  
【摘要】:To enhance the performance of particle swarm optimization(PSO) algorithm for solving constrained optimization problems(COP), constraint consensus vector(CCV) method is introduced to reduce particle's constraint violation for standard PSO algorithm. To prevent boundary violation when a particle moves along the direction of CCV, a direction-preserved method is devised to clamp the CCV, which can also be used to clamp the velocity of particle. Four widely used engineering optimization problems were used to evaluate the proposed CCV-PSO and the optimization results of CCV-PSO were compared to other most recent constrained PSO and genetic algorithm with adaptive constraint handling technique. It is deserved to point out that a new optimal solution of pressure vessel problem is found, which is obviously better than the previously known one.

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