A Multi-objective Discrete PSO Algorithm Based on Enhanced Search

This paper proposes a new multi-objective discrete particle swarm optimization algorithm based on enhanced search (MODPSO-ES). Combined with the global search strategy based on elitist seed repopulation, a new velocity update rule for particles is presented to enhance the exploitation and exploration ability of MODPSO-ES. The performance of MODPSO-ES is verified on four benchmark problems. Empirical studies demonstrate that MODPSO-ES is highly competitive in both approximating the Pareto-optimal front and maintaining the diversity of the solutions on the front.