Abstract:

Considering to solve constrained optimization problems, a hybrid method combining particle swarm optimization (PSO) and simulated annealing (SA) is proposed. The probability jump property of SA is adopted to avoid PSO trapping into local optimum. A feasibilitybased rule is used to solve constrained problems. This rule maybe invalid when the optimum is close to the boundary of constraint conditions, so the new particle containing the information of good infeasible solution is produced in the process of SA. The algorithm is validated using four standard engineering design problems, and the results indicate that PSOSA can find out better optimum.