Optimization of Supply Chain Networks Using MINLP Model with Deterministic Demand

Abdulhadi Altherwi, M. Zohdy
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引用次数: 1

Abstract

This paper aims at investigating the optimization of supply chain networks (SCN) for industrial plants under vendor managed inventory (VMI) policy. The vendor uses Long Range Wide Area Network (LoRaWAN) to minimize the total cost of networks. The problem was developed as a mixed-integer non-linear program (MINLP) model, which helped in reducing the total cost of a VMI, to formulate the coordinated decision issue that incorporates the location inventory issue with the allocation task of LoRaWAN technology and its level of investment. We performed different strategies of investment of LoRaWAN technology of having objective function with three different scenarios: 1) Investment of LoRaWAN technology only in ordering operations; 2) Investment of LoRaWAN technology only in holding operations; 3) Investment of LoRaWAN technology in both holding and ordering operations. The simulation results indicated that the cost-saving obtained by the third scenario is significant due to the least total cost of the objective function as compared with the total cost of the objective function obtained by the first and second scenarios.
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基于需求确定性MINLP模型的供应链网络优化
本文旨在研究供应商管理库存(VMI)策略下工业工厂供应链网络的优化问题。供应商使用远程广域网(LoRaWAN)来最大限度地降低网络的总成本。该问题被发展为一个混合整数非线性规划(MINLP)模型,有助于降低VMI的总成本,以制定协调决策问题,该问题将位置库存问题与LoRaWAN技术的分配任务及其投资水平相结合。我们在三种不同的场景下执行了具有目标函数的LoRaWAN技术的不同投资策略:1)仅在订单操作中投资LoRaWAN;2) 仅在控股业务中投资LoRaWAN技术;3) LoRaWAN技术在控股和订购业务方面的投资。仿真结果表明,与第一和第二场景获得的目标函数的总成本相比,由于目标函数的总体成本最小,因此第三场景获得的成本节约是显著的。
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