Particle Swarm Optimization with Adaptive Mutation Operator

PSO algorithm is one of the useful intelligent algorithms for solving constrained and unconstrained global optimization problems. But a major problem for PSO algorithm is premature convergence in solving multimodal problems. By analyzed the reason of premature convergence, an improved particle swarm optimization (PSO) algorithm based on adaptive mutation operator is developed. The performance of the proposed algorithm is tested by solving two benchmark functions. Experimental results show that the proposed algorithm have better performance.