中文摘要：

将极坐标的思想引入多目标遗传算法来保持解的多样性，由此提出了一种新的多目标遗传算法：PCGA2（Polar Coordinates Genetic AlgorithmsⅡ）；分析了基于极坐标的分布度保持策略的时间复杂度，并通过实验将PCGA2同当前流行的两种多目标遗传算法（NSGA2和SPEA2）进行了比较。实验数据表明该算法不仅在时间耗费上比较低，而且所得到的解具有非常好的分布度。

英文摘要：

A new multi-objective genetic algorithm called PCGA2 （Polar Coordinates Genetic Algorithms Ⅱ ） is proposed in this paper.A strategy based on polar coordinates to keep diversity is introduced into PCGA2.We analyze the time complexity of this strategy.In our experiments,PCGA2 is compared with NSGA2 and SPEA2.The experimental results show that PCGA2 can obtain a good distribution of solutions in short time.