多态性作业车间鲁棒调度CA-GA建模

Research on modeling of robust scheduling for polymorphism job shop based on cellular automata and genetic algorithm

针对多态性作业车间鲁棒调度问题,建立了多态性作业车间鲁棒调度CA-GA模型.根据此类车间多单元布局特点构建作业车间元胞机整体框架,采用遗传算法来优化元胞机的自组织演化规则.考虑到调度的鲁棒性,将鲁棒指标最大完成时间加入模型多目标函数,并以平均松散时间为各个方案鲁棒性的评价指标.最后,将模型应用于PTCN公司生产实例中,通过优化前后的调度方案比较,从加工时间、设备利用率、设备平衡率以及交货期等四个方面验证了该模型的可行性与实用性.

In order to solve the robust scheduling problem for polymorphism job shop, a model based on cellular automata and genetic algorithm is established. To build cellular automata structure according to multi-unit layout feature of polymorphism job shop, then genetic algorithm is used to optimize local self-evolution rules of cellular automata. Considering the scheduling robustness, robust index maximum completion time is included in model multi-objective function, and, robustness of each scheme will be evaluated by slack time. Finally, empirical research of PTCN production workshop scheduling, simulated the production scheduling. Contrasted practical scheme and optimal scheme, optimal scheme reached the better result in processing time, equipment utilization rate, equipment balance rate and delivery time, proving the feasibility and effectiveness of the model and method.