基于遗传算法的多目标动态柔性作业车间调度

Genetic Algorithm for Solving Multi-Objective Dynamic Flexible Job Shop Scheduling

针对国内某玩具厂工模车间调度问题的柔性化、动态化等特点,通过引入虚拟工序和虚拟工时概念对该车间建立调度数学模型。基于周期调度和动态事件调度相结合的调度策略并采用滚动窗口调度工序技术,将动态调度转化为多个连续静态调度窗口,并在静态调度窗口下采用多目标遗传算法解决该类调度模型。给出了不同的动态事件下工序加工的优先级,并根据优先级对染色体的工序排序部分进行编码和反编码。通过对玩具厂工模车间调度的实际运行,验证了动态调度模型、调度策略及所用遗传算法的有效性。

To solve the scheduling problem of mold workshop in a toy factory with dynamic and flexible features, a mathematical model was established by introducing virtual operation and virtual working hours. Based on the strategies of periodic scheduling combined with dynamic event scheduling as well as the rolling window scheduling operation technology, dynamic scheduling was transformed into several continuous static scheduling windows, under which multi-objective genetic algorithm was used to solve the model. The priority of operation scheduling was given in different dynamic events. In addition, the encoding and anti-encoding of chromosome＇s operation sequence were made based on the proposed priority. Real running of mold workshop scheduling verifies the effectiveness of the proposed dynamic scheduling model, scheduling policy and the algorithm.