Two-stage force particle swarm optimization algorithm and application in hydraulic system reliability optimization

Abstract

In view of the particle swarm optimization (PSO) algorithm's shortages of easily trapping into local optimum and premature convergence, an improvement research from the perspective of interaction mechanism among particles is made in this paper. Consider advantages and disadvantages of the current improved PSO algorithms from the aspect of force, the two-stage force particle swarm optimization (TFPSO) algorithm is proposed. The proposed algorithm, which employs staged search strategy to achieve a trade-off between global exploration and local exploitation abilities, divides search process into two stages and constructs corresponding force rules combining with the idea of attractive and repulsive forces in artificial physics. In order to demonstrate the performance of the proposed algorithm in solving optimization problems, TFPSO algorithm is compared with some well-known PSO algorithms in reliability optimization for hydraulic system. Comparison results show that TFPSO algorithm obtains the best optimization results and enhances the performance of PSO in terms of accuracy of the optimal solution and local search ability.