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A new hybrid parallel algorithm for consistent-sized batch splitting job shop scheduling on alternative machines with forbidden intervals

机译:一种新的混合并行算法,用于在具有禁止间隔的替代机器上进行大小一致的批量拆分作业车间调度

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摘要

Considering alternative machines for operations, forbidden intervals during which machines cannot be available and a job’s batch size greater than one in the real manufacturing environment, this paper studies the batch splitting scheduling problem on alternative machines with forbidden intervals, based on the objective to minimize the makespan. A scheduling model is established, taking before-arrival set-up, processing, and transfer time into account. And a new hybrid parallel algorithm, based on differential evolution and genetic algorithm, is brought forward to solve both the batch splitting problem and the batch scheduling problem by assuming a common number of sub-batches in advance. A solution consists of the actual optimum number of sub-batches for each job, the optimum batch size for each sub-batch, and the optimum sequence of operations for these sub-batches. Experiments on the performance of the proposed algorithm under different common numbers of sub-batches are carried out. The results of simulations indicate that the algorithm is feasible and efficient.
机译:考虑到替代机器的运行,在实际制造环境中机器无法使用的禁止间隔以及作业的批量大小大于实际制造环境中的批次数量,本文基于具有最小间隔的目标,研究了在禁止间隔的替代机器上的批次拆分计划问题。制作时间。建立计划模型,将到达前的设置,处理和传输时间考虑在内。提出了一种基于差分进化和遗传算法的混合并行算法,通过预先假设子批的数量相同,可以解决批量拆分问题和批量调度问题。解决方案包括每个作业的实际最佳子批次数量,每个子批次的最佳批次大小以及这些子批次的最佳操作顺序。对该算法在不同的子批公共数目下的性能进行了实验。仿真结果表明了该算法的可行性和有效性。

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