Constrained Optimization PSO Algorithm with Levy Mutation
Liu Chun-an · Xihua Daxue xuebao. Zhexue shehui kexue ban · 2008
A new PSO algorithm (LCPSO) for solving the constrained optimization problems is presented in this paper. The new approach does not require the use of a penalty function, it uses a Levy mutation operator to overcome the defaults of plunging into the local optimal solution by simple PSO. In order to obtain the global optimal solutions, which often locate in the boundary of the constrained region, a new selection operator is introduced based on the constrained conditions of the optimization problem. The new LCPSO can keep the ratio of infeasible solutions in the swarm when selecting the next generation swarm by using the new selection operator. As a result, it can not only increase the diversity of swarm but also avoid the defects of over-penalization and make the swarm approach to the optimal solutions. The numerical experiments show that the proposed algorithm is effective in dealing with the constrained optimization problems.