Abstract: Multi-objective Flexible Job-shop Scheduling Problem（FJSP） is a NP-hard problem.Based on the analysis about it，a mathematical model is built.The model improves multi-objective function which meets more with actual needs.A Hybrid Differential Evolution Algorithm（HDEA） for solving it is designed.According to the differential evolution algorithm easily falling into the local optimum，a method which is used to judge premature convergence is built，and the chaotic optimization is used to solve premature convergence problem to breach the restrictions of local optimization points.Simulation results indicate that the HDEA is efficient，fast and it solves some conflicts of convergence and premature.

Key words: multi-objective, flexible job-shop scheduling problem, differential evolution algorithm, chaos optimization, premature

摘要： 多目标柔性作业车间调度问题属于NP-hard问题。在对该问题进行分析的基础上，为之建立了数学模型，并改进了多目标函数，使其更符合实际需要。提出了一种求解该问题的混合差分演化算法，该算法针对差分演化算法易陷入局部最优现象，提出了算法早熟收敛判定方法，并且利用混沌搜索解决早熟收敛问题，突破了局部极值的限制以再次寻优计算。仿真结果表明，该算法效率高，寻优速度快，有效地解决了收敛性能和早熟之间的矛盾。

关键词: 多目标, 柔性作业车间调度问题, 差分演化算法, 混沌优化, 早熟