Abstract: Diversity of solutions is one of the most important jobs of multi-objective optimization.Diversity includes the span and uniformity.In Multi-Objective Evolutionary Algorithms（MOEAs），population maintenance is used to realize the diversity.In this paper，a ∞-norm（infinite norm） based stepwise（INS） method is proposed to increase diversity of MOEAs.INS use ∞-norm as a measurement of diversity of individuals，and use stepwise method to wipe off individuals form population.Through experiments on 9 test problems，compared with two most popular MOEAs——NSGA-II and ε-MOEA，the experimental results demonstrate that INS can increase diversity of solutions obviously.

摘要： 解集的分布性是多目标优化中最重要的研究工作之一，解集的分布性主要体现在两个方面，一是解集的分布广度；二是解集的均匀性。在多目标进化算法（MOEAs）中，解集分布性的保持放在种群维护中实现，提出一种基于∞范数的逐步方法（INS）来提高MOEAs解集的分布性，INS用∞范数来衡量个体的分布性，用逐步的方法来裁剪个体。通过与目前最流行的两个MOEAs——NSGA-II和ε-MOEA，在9个测试函数上进行实验，结果表明INS能很好地提高解集的分布性。