针对车间作业的加工受到机床、操作工人等双资源制约条件下出现多种扰动的JSP调度问题,提出了基于受控Petri网和GASA对不同扰动进行分类处理的新方法。首先通过构建带有控制器的Petri网模型使系统的运行满足期望的目标,然后基于该模型把遗传算法和模拟退火算法相结合,以最小化最大完工时间为目标,基于机床故障修复时间、工人离岗时间及取消订单包含任务的多少进行分类调度,然后根据扰动恢复后剩余任务的多少决定是否进行再次调度,避免大范围调整造成的生产不稳定状态,最大限度的维持车间的生产能力。最后通过实例验证了算法的有效性和可行性。 Aiming at the JSP job scheduling problem which is caused by many kinds of disturbances under the condition of dual resources, such as machine tool and operating worker, a new method of classifying different disturbances based on controlled Petri net and GASA is proposed. First, the system is operated to meet the desired goal by constructing a Petri net model with controller. Then based on the model, genetic algorithm and simulated annealing algorithm are combined to minimize the maximum completion time. Based on the time of machine fault repair, Departure time and cancellation order contains the number of tasks to carry on the classified scheduling, and then decide whether to re-schedule according to the remaining tasks after disturbance recovery, to avoid the production instability caused by the large-scale adjustment and to maximize the production capacity of the workshop. Finally, an example is given to verify the effectiveness and feasibility of the algorithm.