Abstract: To overcome the shortcomings of partial multiobjective evolutionary algorithms,we combine some outstanding thoughts in SPEA2 and immune multi-objective optimization algorithm then innovate out a Pareto-based multi-object clonal evolutionary algorithm NPCA(non-dominated Pareto clonal algorithm). And testing the algorithm with the famous multi-objective optimization problems ZDTand DTLZ, the results show that the new algorithm NPCA obviously takes advantages over the typical multi-objective evolutionary algorithms.

Key words: MOP(Multi objective optimization problems)，MOEA(Multi-objective evolutionary algorithms)，Multi-objective optimization immune algorithms,NPCA(Non-dominated Pareto clonal algorithm)