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Planning on Discrete Event Systems using parallelism maximization

机译:使用并行最大化的离散事件系统规划

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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.
机译:这项工作涉及在离散事件系统中的生产计划问题,利用监督控制理论来确定搜索空间,并根据并行性的最大化来开发两个启发式,找到最小化MEPESPAN的序列。 监督控制理论的作用是提供由闭环行为给出的所有安全生产序列的集合。 这两个启发式基于该想法,即应该在允许的情况下立即执行可控事件(最大化并行性),而是仅评估时间上可行的候选者。 所提出的方法提供了在模型参数中的不确定性的稳健性提供了代表工厂操作所需的时间间隔的解决方案。 虽然不能保证启发式程序一般地达到精确的最佳解决方案,但我们展示了一个案例研究,以为所有批量尺寸发生。 案例研究还示出了计算时间方面的效率。

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