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Bottleneck-based Heuristics To Minimize Tardy Jobs In A Flexible Flow Line With Unrelated Parallel Machines

机译:基于瓶颈的启发式算法可在不相关并行机的情况下最大限度地减少柔性流水线中的拖延作业

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This paper develops new bottleneck-based heuristics with machine selection rules to solve the flexible flow line problem with unrelated parallel machines in each stage and a bottleneck stage in the flow line. The objective is to minimize the number of tardy jobs in the problem. The heuristics consist of three steps: (1) identifying the bottleneck stage; (2) scheduling jobs at the bottleneck stage and the upstream stages ahead of the bottleneck stage; (3) using dispatching rules to schedule jobs at the downstream stages behind the bottleneck stage. A new approach is developed to find the arrival times of the jobs at the bottleneck stage, and two decision rules are developed to schedule the jobs on the bottleneck stage. This new approach neatly overcomes the difficulty of determining feasible arrival times of jobs at the bottleneck stage. In order to evaluate the performance of the proposed heuristics, six well-known dispatching rules are examined for comparison purposes. Six factors are used to design 729 production scenarios, and ten test problems are generated for each scenario. Computational results show that the proposed heuristics significantly outperform all the well-known dispatching rules. An analysis of the experimental factors is also performed and several interesting insights into the heuristics are discovered.
机译:本文使用机器选择规则开发了新的基于瓶颈的启发式方法,以解决每个阶段无关的并行机器以及流线瓶颈阶段的柔性流线问题。目的是最大程度地减少问题中迟到的工作数量。启发式方法包括三个步骤:(1)识别瓶颈阶段; (2)在瓶颈阶段和上游阶段提前安排工作; (3)使用调度规则在瓶颈阶段之后的下游阶段调度作业。开发了一种新方法来查找瓶颈阶段的作业到达时间,并开发了两个决策规则来安排瓶颈阶段的作业。这种新方法巧妙地克服了在瓶颈阶段确定可行的工作到达时间的困难。为了评估所提出的启发式方法的性能,为了比较起见,检查了六个众所周知的调度规则。六个因素用于设计729个生产方案,并且为每个方案生成十个测试问题。计算结果表明,所提出的启发式算法明显优于所有众所周知的调度规则。还对实验因素进行了分析,并发现了一些启发式的有趣见解。

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