关键词: 粒子群, 多目标进化算法, Pareto最优, 精英策略, 归档技术

Abstract: An Improved Multi-Objective Particle Swarm Optimization（IMOPSO） algorithm is proposed，in which elitism archived strategy is used，global best position is provided by non-dominated solutions in the archive and individual best position is updated based on Pareto dominance.The algorithm uses objective solutions linear density to measure non-dominated solutions quality and employs the strategy of deleting low density non-dominated solutions to enhance non-dominated solutions uniformity.To overcome the shortcoming of theoretical index in multi-objective evolution algorithm，a practical index is developed.Simulation results on benchmark functions show the proposed method can obtain a lot of non-dominated solutions，rapidly converge to the Pareto front and uniformly spread along the front.

Key words: particle swarm, multi-objective evolutionary algorithm, Pareto optimal, elitism strategy, archive technique