An optimal ordering and replenishment policy for a vendor-buyer system under varying replenishment intervals and delayed payment

A. Taleizadeh, H. Zarei, B. Sarker
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引用次数: 9

Abstract

The replenishment intervals can be probabilistic when the system or the supplier has problem with manufacturing or shipping the goods. In this paper, an economic order quantity (EOQ) model with probabilistic replenishment intervals and permissible delay in payments with partial backordering is developed. This paper considers three different possible situations and suggests optimal inventory policy for each situation separately regarding the amount of expected order quantity and replenishment-up-to level that maximises the expected cyclic profit for the buyers. The model is analysed for the uniform and exponential probability distribution functions (PDF) for time of replenishment and a closed-form solution is achieved in all cases. Finally, a sensitivity analysis is performed to know the general functional behaviour and to clarify the applicability of the proposed model when the system behaviour is unstable. The results indicate that a customer can obtain the optimum replenishment-up-to level and order quantity when the replenishment intervals is probabilistic in three different possible situations. [Received: 17 August 2017; Revised: 10 January 2018; Revised: 23 August 2018; Accepted: 11 November 2018]
不同补货间隔和延迟付款条件下的最优订货和补货策略
当系统或供应商在制造或运输货物时出现问题时,补货间隔可能是概率性的。本文建立了具有概率补货间隔和允许延迟付款的部分延期订货的经济订货量模型。本文考虑了三种不同的可能情况,并针对每种情况分别提出了最优库存策略,即期望订货量和补货量达到最大的期望周期利润水平。对该模型进行了补货时间均匀概率分布函数和指数概率分布函数的分析,得到了所有情况下的封闭解。最后,进行了灵敏度分析,以了解一般的功能行为,并阐明了当系统行为不稳定时所提出的模型的适用性。结果表明,在三种不同的可能情况下,当补货间隔为概率时,客户可以获得最优的补货数量和订单数量。[收稿日期:2017年8月17日;修订日期:2018年1月10日;修订日期:2018年8月23日;录用日期:2018年11月11日]
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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