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Flexible Job Shop Scheduling with Multi-level Job Structures

机译:具有多级作业结构的灵活的作业车间调度

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This paper deals with a scheduling problem in a flexible job shop with multi-level job structures where end products are assembled from sub-assemblies or manufactured components. For such shops MRP (Material Requirement Planning) logic is frequently used to synchronize and pace the production activities for the required parts. However, in MRP, the planning of operational-level activities is left to short term scheduling. So, we need a good scheduling algorithm to generate feasible schedules taking into account shop floor characteristics and multi-level job structures used in MRP. In this paper, we present a GA (Genetic Algorithm) solution for this complex scheduling problem based on a new gene to reflect the machine assignment, operation sequences and the levels of the operations relative to final assembly operation. The relative operation level is the control parameter that paces the completion timing of the components belonging to the same branch in the multi-level job hierarchy. We compare the genetic algorithm with several dispatching rules in terms of total tardiness and the genetic algorithm shows outstanding performance for about forty modified standard job-shop problem instances.
机译:本文讨论的是具有多层作业结构的柔性作业车间中的调度问题,其中最终产品由子装配体或制造的组件装配而成。对于此类商店,经常使用MRP(物料需求计划)逻辑来同步和调整所需零件的生产活动。但是,在MRP中,运营级别活动的计划留给短期计划进行。因此,我们需要一种良好的调度算法来生成可行的调度,其中要考虑MRP中使用的车间特征和多层作业结构。在本文中,我们提出了一种基于新基因的GA(遗传算法)解决方案,该解决方案基于一个新基因来反映机器分配,操作顺序以及相对于最终装配操作的操作级别。相对操作级别是控制参数,用于控制多级作业层次结构中属于同一分支的组件的完成时间。我们将遗传算法与几种调度规则进行了总拖后处理的比较,并且该遗传算法在大约40个修改后的标准Job-shop问题实例中显示了出色的性能。

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