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A similarity score-based two-phase heuristic approach to solve the dynamic cellular facility layout for manufacturing systems

机译:基于相似的分数的两相启发式方法来解决制造系统的动态蜂窝设备布局

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摘要

The dynamic cellular facility layout problem (DCFLP) is a well-known NP-hard problem. It has been estimated that the efficient design of DCFLP reduces the manufacturing cost of products by maintaining the minimum material flow among all machines in all cells, as the material flow contributes around 10-30% of the total product cost. However, being NP hard, solving the DCFLP optimally is very difficult in reasonable time. Therefore, this article proposes a novel similarity score-based two-phase heuristic approach to solve the DCFLP optimally considering multiple products in multiple times to be manufactured in the manufacturing layout. In the first phase of the proposed heuristic, a machine-cell cluster is created based on similarity scores between machines. This is provided as an input to the second phase to minimize inter/intracell material handling costs and rearrangement costs over the entire planning period. The solution methodology of the proposed approach is demonstrated. To show the efficiency of the two-phase heuristic approach, 21 instances are generated and solved using the optimization software package LINGO. The results show that the proposed approach can optimally solve the DCFLP in reasonable time.
机译:动态蜂窝设施布局问题(DCFLP)是众所周知的NP难题问题。据估计,DCFLP的有效设计通过维持所有细胞中所有机器中的最小材料流量来降低产品的制造成本,因为材料流量占总产品成本的10-30%。然而,在合理的时间内最佳地解决DCFLP非常困难。因此,本文提出了一种基于新的相似性评分的两相启发式方法,可以在多次上最佳地考虑多次产品的DCFLP。在提出启发式的第一阶段,基于机器之间的相似性分数来创建机器单元集群。这是作为第二阶段的输入提供,以最小化整个规划期间的间/内部材料处理成本和重新排列成本。证明了所提出方法的解决方案方法。为了展示两相启发式方法的效率,使用优化软件包Lingo生成和解决了21个实例。结果表明,该方法可以在合理的时间内最佳地解决DCFLP。

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