Abstract: Since the local convergence was often found in the process that the PSO algorithm is used to deal with multiobjective optimization problems, an new algorithm based on Maximin PSO algorithm is presented for multiobjective PSO, where the swarm size is adjusted dynamically to avoid converging at a false Pareto optimal solutions. Meanwhile, the relative fitness variance of particle is introduced into the formula of Maximin to get rid of the effect of reducing the diversity of particle swarm. Then, based on the idea about Pareto optimum, the variance Maximin strategy is used to evaluate the optimal solutions and the non-dominated solutions are stored in a size-variable elitism repository so as to provide a good diversity in its solutions. Experimental results showed the feasibility of the algorithm in solving complicated multi-objective optimization in industry.