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Genetic Programming with Delayed Routing forMultiobjective Dynamic Flexible Job Shop Scheduling

机译：延迟路由型制备动态柔性作业商店调度的遗传编程

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Dynamic Flexible Job Shop Scheduling (DFJSS) is an important and challenging problem, and can have multiple conflicting objectives. Genetic Programming Hyper-Heuristic (GPHH) is a promising approach to fast respond to the dynamic and unpredictable events in DFJSS. A GPHH algorithm evolves dispatching rules (DRs) that are used to make decisions during the scheduling process (i.e., the so-called heuristic template). In DFJSS, there are two kinds of scheduling decisions: the routing decision that allocates each operation to a machine to process it, and the sequencing decision that selects the next job to be processed by each idle machine. The traditional heuristic template makes both routing and sequencing decisions in a non-delay manner, which may have limitations in handling the dynamic environment. In this article, we propose a novel heuristic template that delays the routing decisions rather than making them immediately. This way, all the decisions can be made under the latest and most accurate information. We propose three different delayed routing strategies, and automatically evolve the rules in the heuristic template by GPHH. We evaluate the newly proposed GPHH with Delayed Routing (GPHH-DR) on a multiobjective DFJSS that optimises the energy efficiency and mean tardiness. The experimental results show that GPHH-DR significantly outperformed the state-of-the-art GPHH methods. We further demonstrated the efficacy of the proposed heuristic template with delayed routing, which suggests the importance of delaying the routing decisions.
机译：动态灵活的作业商店计划（DFJSS）是一个重要而充满挑战性的问题，并且可以具有多种相互矛盾的目标。遗传编程超高启发式（GPHH）是快速响应DFJSS中动态和不可预测的事件的有希望的方法。 GPHH算法演变了用于在调度过程（即，所谓的启发式模板）期间进行决定的调度规则（DRS）。在DFJS中，有两种调度决策：将每个操作分配给计算机以处理它的路由决定以及选择由每个空闲计算机处理的下一个作业的排序决定。传统的启发式模板以非延迟方式进行路由和排序决策，这可能有限制处理动态环境。在本文中，我们提出了一种新的启发式模板，延迟了路由决策，而不是立即制作它们。这样，所有决定都可以在最新和最准确的信息下进行。我们提出了三种不同的延迟路由策略，并通过GPHH自动在启发式模板中的规则。我们在多目标DFJ上评估了新提出的GPHH（GPHH-DR），这些DFJSS优化了能量效率和均值迟到。实验结果表明，GPHH-DR显着优于最先进的GPHH方法。我们进一步展示了拟议的启发式模板与延迟路由的功效，这表明延迟了路由决策的重要性。

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