基于Petri网和GASA的双资源JSP动态优化调度

以带有控制器的Petri网为建模工具对柔性生产调度中的离散事件建模.该模型不仅能够反映柔性生产线上待加工产品的多条工艺加工路径及其资源约束,还可以对系统的设备维护、各种优先级等特性进行描述.利用遗传算法和模拟退火算法(GASA)获得调度结果,用于解决作业车间在机床、操作工人等生产资源制约条件下的动态优化调度.该调度以生产周期为目标,通过多种交叉、变异、概率更新、再分配策略等遗传和模拟退火操作,得到目标的最优或次优解;尤其重要的是该算法能够在扰动发生后迅速提供新的调度计划.对算法进行了仿真研究,结果表明该算法是可行、有效的.

Dynamic Scheduling Optimization of Dual-Resource Based on Petri Net and GASA

Petri net with controller is used to model the discrete events in flexible job shop scheduling.The model is available to not only show the multiprocessing paths for the jobs to be processed and resource constrains on a flexible line,but also depict the system characteristics,such as equipment maintenance and different types of priorities.The scheduling results are based on GASA(genetic and simulated annealing algorithm) and used to address the dynamic optimal scheduling in the job shop where the machines and workers are both constrained.Taking minimizing the make-span as the objective of scheduling,an optimal or suboptimal solution to the scheduling is found through various genetic and simulated annealing operations as crossover,mutation,probabilistic updating and re-assignment strategy;especially the GASA algorithm which will provide renewed schedule rapidly after an unexpected disturbance happened in job shop.Simulation results based on some job shop scheduling show that the GASA is efficient and robust.