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A Batch Splitting Job Shop Scheduling Problem with bounded batch sizes under Multiple-resource Constraints using Genetic Algorithm

机译:使用遗传算法在多元资源约束下的有界批量大小的批量分离作业商店调度问题

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Considering alternative resources for operations, requirement of multiple resources to process an operation and a job's batch size greater than one in the real manufacturing environment, a study is made on the batch splitting scheduling problem with bounded batch sizes under multiple-resource constraints, based on the objective to minimize the maximum completion time. A genetic algorithm which is suitable for this problem is proposed, with a new chromosome representation, which takes into account the batch splitting of the original batches of jobs. And a new crossover method and a new mutation method are proposed based on the new chromosome representation. The results of the simulation indicate that the method is feasible and efficient.
机译:考虑到运营的替代资源,需要多个资源处理操作的多个资源以及真实制造环境中的作业的批量大小,基于多重资源约束下的批量批量尺寸的批量分割调度问题进行了研究。目的是最小化最大完成时间。提出了一种适用于该问题的遗传算法,具有新的染色体表示,这考虑了原始作业批次的批量分裂。基于新的染色体表示,提出了一种新的交叉方法和新的突变方法。模拟结果表明该方法是可行和有效的。

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