This work deals with the production planning problem in Discrete Event Systems, using the Supervisory Control Theory to establish the search space and developing two heuristics based on the maximization of the parallelism to find sequences that minimize makespan. The role of the Supervisory Control Theory is to provide the set of all safe production sequences, given by the closed-loop behavior. The two heuristics are based on the idea that controllable events should be executed as soon as they are allowed (maximizing parallelism) but only temporally feasible candidates are evaluated. The proposed methodology delivers solutions that are robust to uncertainties in the model parameters that represent time intervals required for plant operations. Although heuristic procedures are not guaranteed to reach exact optimal solutions in general, we present a case study where it happens for all batch sizes. The efficiency in terms of computation time is also illustrated by the case study.

这项工作处理离散事件系统中的生产计划问题，使用监督控制理论建立搜索空间，并在并行度最大化的基础上开发两种启发式算法，以找到使制造期最小化的序列。监督控制理论的作用是提供所有安全生产顺序的集合，由闭环行为给出。两种启发式方法基于这样的思想：可控制事件应在允许事件发生后立即执行（最大化并行性），但仅评估时间上可行的候选对象。所提出的方法论提供了对于代表工厂运行所需时间间隔的模型参数不确定性具有鲁棒性的解决方案。虽然一般不能保证启发式程序可以达到确切的最佳解决方案，我们提供了一个案例研究，其中涉及所有批次大小的情况。案例研究还说明了在计算时间方面的效率。