Taguchi-based disturbance with tournament selection to improve on MOPSO
In this paper, a Taguchi-based disturbance mechanism is deployed in our preliminary study on MOPSO. The proposed scenario includes tournament selection for global best solutions, jump-improved operation to expand the searching space, cluster operation to improve the diversity, and Taguchi-based disturbance can enhance the searching ability and reduce the possibility of falling into local optima of particles. Experiments are conducted on seven two-objective benchmarks. The results show that the proposed method operates better than other algorithms in three performance metrics.