Dynamic job-shop scheduling with urgent orders based on Petri net and GASA

A new scheduling method based on the controlled Petri net and GASA is proposed to the job-shop scheduling problem (JSP) with urgent orders constrained by machines, workers. Firstly, a Petri net with controller is modeled in flexible job shop scheduling problem, not only does it have the modeling capability of a traditional Petri net, but also it depicts system characteristics, such as equipment maintenance, different types of priorities, and so on. It is flexible in responding to unexpected scenario changes and is thus robust to system disturbances. Then, the hybrid genetic algorithm and simulated annealing algorithm (GASA) is applied based on the controlled Petri net model. Function objective of the proposed method is to minimize the completion time. When urgent order comes, remainder jobs and urgent jobs are disposed separately, then making integration, and through finding optimal results of remainder jobs based on urgent jobs result is optimal, the whole and local optimal results can be found through this method. Scheduling example is employed to illustrate the effectiveness of the method.