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A new multi-objective evolutionary algorithm, called selective migration parallel genetic algorithm (SMPGA) was presented in this paper, which designs a new migration strategy and qualification based on the adaptive grid. In SMPGA, a searching population and a elite population evolve at the same time; unique migration strategy and qualification are used to keep and improve the convergence and diversity of the Pareto optimal set. Besides, according to their different purposes, the two populations adopt different crossover strength. Simulation results show that SMPGA can find accurate and uniform Pareto optimal solutions on different multi-objective problems.