中文摘要：

将差分进化算法用于多目标优化问题,提出了多目标混沌差分进化算法（CDEMO）.该算法利用混沌序列初始化种群,并用混沌备用种群进行替换操作.该操作不仅起到了维持非劣最优解集均匀性的作用,而且增强了算法的搜索功能.对CDEMO的性能进行研究,数值实验结果表明了CDEMO的有效性.

英文摘要：

By using differential evolution algorithm to solve multiobjective optimization problems, chaotic differential evolution for multiobjective optimization （CDEMO） is proposed. Chaotic sequences are used in the initialization of the evolutionary population and chaotic population candidate is created with chaotic variables to be used in substitution operation. The operation not only helps to maintain uniformity of the Pareto optimal solution set, but enhances the algorithm＇s searching ability. The optimization performance of CDEMO is evaluated and numerical experimental results show the effectiveness of the proposed method.