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CAR: heuristics for the inventory routing problem
Wireless Networks ( IF 3 ) Pub Date : 2020-01-23 , DOI: 10.1007/s11276-020-02259-6
Ramkumar Nambirajan , Abraham Mendoza , Subramanian Pazhani , T. T. Narendran , K. Ganesh

Vendor managed inventory (VMI) is a streamlined approach to inventory and order fulfillment and is a system in which vendors continuously and automatically replenish a trading partner’s inventory. Vendors must ensure appropriate quantities of storages at the point of demand and must ensure optimal distribution plans, including routing of the distribution vehicles. This problem is known as the inventory routing problem (IRP) and seeks to integrate the routing of vehicles used for collection and distribution, with conventional inventory management. This paper addresses an IRP with a manufacturer that supplies a product using a fleet of vehicles to a set of warehouses over a defined time horizon. We develop a mixed integer linear program to determine the optimal allocation and the routing schedule for warehouses over the defined time horizon. To solve this problem, we propose a three-phase heuristic approach, called CAR: clustering of receiver nodes, allocation of quantities to these nodes, and routing of delivery vehicles through clusters of nodes. Computational studies are carried out and experimental trials conducted over a large number of data sets provide encouraging results and show usefulness of the solution approaches. The proposed ILP would provide optimal solution to the problem but it demands huge computational effort. However, CAR2, a proposed heuristic, is able to get solutions 7.41% better than the upper bound solutions obtained from CPLEX. These approaches can easily be implemented into existing VMI systems.



中文翻译:

CAR:库存路由问题的启发式方法

供应商管理的库存(VMI)是简化库存和订单履行的方法,并且是一个系统,供应商可以在该系统中连续自动地补充贸易伙伴的库存。供应商必须在需求点确保适当数量的存储,并且必须确保最佳的分配计划,包括分配车辆的路线。这个问题被称为库存路由问题(IRP),它试图将用于收集和分配的车辆的路由与常规库存管理相集成。本文针对的是制造商的IRP,该制造商在规定的时间范围内使用一组车辆向一组仓库提供产品。我们开发了一个混合整数线性程序,以确定在定义的时间范围内仓库的最佳分配和路由计划。为了解决这个问题,我们提出了一种称为CAR的三相启发式方法:对接收器节点进行聚类,向这些节点分配数量,以及通过节点的聚类路由运送车辆。进行了计算研究,并且对大量数据进行的实验性试验提供了令人鼓舞的结果,并显示了解决方案的实用性。提出的ILP将为该问题提供最佳解决方案,但需要大量的计算工作。但是,CAR2(一种拟议的启发式方法)能够比从CPLEX获得的上限解决方案好7.41%。这些方法可以轻松地实现到现有的VMI系统中。并通过节点集群对运送车辆进行路由。进行了计算研究,并且对大量数据进行的实验性试验提供了令人鼓舞的结果,并显示了解决方案的实用性。提出的ILP将为该问题提供最佳解决方案,但需要大量的计算工作。但是,CAR2(一种拟议的启发式方法)能够比从CPLEX获得的上限解决方案好7.41%。这些方法可以轻松地实现到现有的VMI系统中。并通过节点集群对运输工具进行路由。进行了计算研究,并且对大量数据进行的实验性试验提供了令人鼓舞的结果,并显示了解决方案的实用性。提出的ILP将为该问题提供最佳解决方案,但需要大量的计算工作。但是,CAR2(一种拟议的启发式方法)能够比从CPLEX获得的上限解决方案好7.41%。这些方法可以轻松地实现到现有的VMI系统中。提出的ILP将为该问题提供最佳解决方案,但需要大量的计算工作。但是,CAR2(一种拟议的启发式方法)能够比从CPLEX获得的上限解决方案好7.41%。这些方法可以轻松地实现到现有的VMI系统中。提出的ILP将为该问题提供最佳解决方案,但需要大量的计算工作。但是,CAR2(一种拟议的启发式方法)能够比从CPLEX获得的上限解决方案好7.41%。这些方法可以轻松地实现到现有的VMI系统中。

更新日期:2020-01-23
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