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Two-stage assembly flow-shop scheduling problem with non-identical assembly machines considering setup times

机译:考虑设置时间的不相同组装机的两阶段组装流水车间调度问题

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In this paper, we address the two stage assembly flow-shop problem with multiple non-identical assembly machines in stage two to minimise weighted sum of makespan and mean completion time. Also, sequence dependent setup times are considered for the first stage. This problem is a generalisation of previously proposed two stage assembly flow-shop problems (TSAFSP). In many real world industrial and production systems, there is more than one assembly machine to assemble job components. After extending a mathematical mixed-integer linear programming model to solve the problem, we use GAMS software. The TSAFSP has been known as NP-hard. Therefore, our more general problem is NP-hard too and so for large sized problems the right way to proceed is with the use of heuristic algorithms. So in this paper a hybrid VNS heuristic, which is a combination of the variable neighbourhood search (VNS) algorithm and a novel heuristic is developed and its solutions compared with solutions obtained by GAMS. Computational experiments reveal that the hybrid VNS heuristic performs much better than GAMS with respect to the percentage errors and run times.
机译:在本文中,我们使用第二阶段中的多个不相同的组装机解决了两阶段的组装流水车间问题,以最大程度地减少工期的加权总和和平均完成时间。同样,在第一阶段考虑与序列有关的建立时间。此问题是先前提出的两阶段装配流水车间问题(TSAFSP)的概括。在许多现实世界的工业和生产系统中,有不止一台组装机来组装作业组件。在扩展数学混合整数线性规划模型以解决该问题后,我们使用GAMS软件。 TSAFSP被称为NP-hard。因此,我们更普遍的问题也是NP-hard,因此对于大型问题,正确的处理方法是使用启发式算法。因此,在本文中,开发了一种混合VNS启发式算法,该算法是可变邻域搜索(VNS)算法和一种新颖的启发式算法的组合,其解决方案与GAMS获得的解决方案相比较。计算实验表明,就百分比误差和运行时间而言,混合VNS启发式算法的性能比GAMS好得多。

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