Multi-objective Particle Swarm Optimization Algorithm Based on the Disturbance Operation

Abstract

To overcome the defect of wide-ranged exploration for particle swarm optimization, a kind of multi-objective particle swarm optimization algorithm with disturbance operation(MPSOD) is proposed. It employs particle swarm optimization and disturbance operation to generate new population in order to enhance the wide-ranged exploration for particle swarm optimization algorithm. Numerical experiments are compared with NSGA-II, SPEA2 and IVIOPSO On six benchmark problems. The numerical results show the effectiveness of the proposed MPSOD algorithm.