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Earliness-tardiness minimization on scheduling a batch processing machine with non-identical job sizes

机译:在调度具有不同作业大小的批处理机器时,将尽早拖延最小化

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This paper considers the scheduling problem of minimizing earliness-tardiness (E/T) on a single batch processing machine with a common due date. The problem is extended to the environment of non-identical job sizes. First, a mathematical model is formulated, which is tested effectively under IBM ILOG CPLEX using the constraint programming solver. Then several optimal properties are given to schedule batches effectively, and by introducing the concept of ARB (Attribute Ratio of Batch), it is proven that the ARB of each batch should be made as small as possible in order to minimize the objective, designed as the heuristic information for assigning jobs into batches. Based on these properties, a heuristic algorithm MARB (Minimum Attribute Ratio of Batch) for batch forming is proposed, and a hybrid genetic algorithm is developed for the problem under study by combining GA (genetic algorithm) with MARB. Experimental results demonstrate that the proposed algorithm outperforms other algorithms in the literature, both for small and large problem instances.
机译:本文考虑了在具有共同到期日的单批处理机器上使提前/拖后处理(E / T)最小化的调度问题。问题扩展到工作大小不同的环境。首先,制定数学模型,并使用约束编程求解器在IBM ILOG CPLEX下对其进行有效测试。然后给出了几个最佳属性以有效地调度批次,并且通过引入ARB(批次的属性比率)的概念,证明了应将每个批次的ARB尽可能小以最小化目标,设计如下分批分配作业的启发式信息。基于这些特性,提出了一种启发式的批处理最小化算法MARB(批处理的最小属性比率),并通过将遗传算法(GA)与MARB相结合,为研究中的问题开发了一种混合遗传算法。实验结果表明,无论是小问题还是大问题,该算法均优于文献中的其他算法。

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