Multi-objective mean particle swarm optimization algorithm

Abstract

In this paper, Pareto non-dominated ranking, crowding distance, tournament selection methods and mean particle swarm optimization were introduced, we using these concepts, a novel mean particle swarm optimization algorithm for multi-objective optimization problem is proposed. Finally, three standard non-constrained multi-objective functions and four constrained multi-objective functions are used to test the performance of the algorithm. The experiment results show that the proposed approach is an efficient and feasible.