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A heuristic model for dynamic flexible job shop scheduling problem considering variable processing times

机译：考虑可变处理时间的动态柔性作业车间调度问题的启发式模型

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摘要

In real scheduling problems, unexpected changes may occur frequently such as changes in task features. These changes cause deviation from primary scheduling. In this article, a heuristic model, inspired from Artificial Bee Colony algorithm, is proposed for a dynamic flexible job-shop scheduling (DFJSP) problem. This problem consists of n jobs that should be processed by m machines and the processing time of jobs deviates from estimated times. The objective is near-optimal scheduling after any change in tasks in order to minimise the maximal completion time (Makespan). In the proposed model, first, scheduling is done according to the estimated processing times and then re-scheduling is performed after determining the exact ones considering machine set-up. In order to evaluate the performance of the proposed model, some numerical experiments are designed in small, medium and large sizes in different levels of changes in processing times and statistical results illustrate the efficiency of the proposed algorithm.
机译：在实际的计划问题中，意外的更改可能经常发生，例如任务功能的更改。这些更改导致与主要计划的偏离。本文提出了一种启发式模型，该模型受人工蜂群算法启发，用于动态柔性作业车间调度（DFJSP）问题。此问题包括应由m台机器处理的n个作业，并且作业的处理时间与估计时间不同。目标是在任务发生任何更改后进行接近最佳的计划，以最大程度地缩短最大完成时间（Makespan）。在提出的模型中，首先，根据估计的处理时间进行调度，然后在考虑机器设置确定了确切的时间之后，进行重新调度。为了评估所提出模型的性能，设计了一些数值实验，分别以小，中，大尺寸在处理时间变化的不同水平上进行统计，统计结果说明了所提出算法的效率。

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