中文摘要：

提出一种基于滚动窗口的多目标遗传算法调度优化策略，该策略采用基于周期和事件驱动的混合再调度机制将调度过程分成连续静态调度区间，在每个区间内用基于Pareto概念的多目标进化算法对窗口工件进行调度优化。根据动态调度问题的特性，设计了有效的解码和遗传操作，并以常用的动态调度性能指标（交货期、最大流经时间、最大完工时间以及初始调度的偏离程度）为多目标遗传算法为优化指标。此外，为了降低计算的复杂性和维持生产的稳定性，提出一种人机协同动态调度机制。基于上述策略开发出多目标动态调度原型系统，通过对动态实例进行测试，验证了该策略的有效性和可行性。

英文摘要：

An improved multi--objective genetic algorithm based on rolling--horizon procedure was proposed. In this procedure, periodic and event driven rescheduling strategies were employed and the dynamic scheduling problem was decomposed into a series of continual and static scheduling problems, then an improve multi--objective genetic algorithm were applied to optimize each of the static scheduling problems. According to the characteristics of the dynamic scheduling problem, the efficient decoding procedure and genetic operators were presented for the improved multi--objective genetic algorithm, and the objectives of rescheduling were to minimize the makespan, total tardiness, the mean flow--time, deviations from the pre--schedule. In order to adapt to the complex manufacturing environment and sustain the stability of production, a human--computer collaborative scheduling procedure was presented for the implementation of the scheduling process. The approach was tested on the improved benchmark instance by the scheduling prototype system developed, and the simulation resuits validate the effectiveness of the proposed strategies.