供应商管理库存系统下的库存路由方法

A. Borade, S. Bansod
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引用次数: 1

摘要

供应商管理库存是一种协作性的业务实践,被组织采用以提高业务绩效。在这种做法下,零售商与制造商共享需求和其他相关信息,制造商反过来管理零售商的库存。在这种情况下,制造商有责任决定交货的大小和时间、车辆路线等。本研究探讨供应商管理的库存实践,特别是库存路线问题,零售商和制造商,当有很大的波动的日常需求。针对供应商管理库存系统中需求超过有限生产能力的库存补充问题,在MATLAB中构建了一个数值实验,利用模糊最小-最大学习算法找到了最优的日需求分布和车辆路径。首先,利用模糊集超框来确定向零售商交付数量的顺序,然后利用折扣系数进行分配。最后,采用模糊迭代算法实现路由。本文的重点是证明我们的方法的有效性,并将结果与简单的贪婪启发式方法进行比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An approach for inventory routing under vendor managed inventory system
Vendor managed inventory is a collaborative business practice adopted by organisations to improve the business performance. Under this practice, the retailers share demand and other related information with the manufacturer, who in turn manages the inventory of the retailer. In such event, the manufacturer assumes the responsibility of taking the decisions about size and time of delivery, vehicle routing, etc. This study examines the vendor managed inventory practice, specifically inventory routing problem, for retailers and a manufacturer when there is a wide fluctuation of daily demand. We have addressed a special issue related to inventory replenishment in vendor managed inventory system, where demand exceeds the finite production capacity .We construct a numerical experiment in MATLAB to find the optimal daily demand distribution and vehicle routing using fuzzy min-max learning algorithm. First, for deciding the sequence in which the quantity to be delivered to the retailers, a fuzzy set hyperboxes are used .Then, assignment is done with the help of discounting coefficient. Lastly, routing is done using fuzzy iterative algorithm. The focus of this paper is on demonstrating the effectiveness of our approach and comparing the results with that of simple greedy heuristics.
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