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Exact Analysis of Capacitated Two-Echelon Inventory Systems with Priorities

机译:具有优先级的能力两级库存系统的精确分析

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We consider a two-echelon inventory system with a capacitated centralized production facility and several distribution centers (DCs). Both production and transportation times are stochastic with general distributions. Demand arrives at each DC according to an independent Poisson process and is backlogged if the DC is out of stock. We allow different holding and backlog costs at the different DCs. We assume that inventory at DCs is managed using the one-for-one replenishment policy. The main objective of this paper is to investigate the control of the multiechelon M/G/1 setting with general transportation times. To achieve this objective, we analyze several decentralized allocation policies including the first-come, first-served (FCFS), strict priority (SP), and multilevel rationing (MR) policies. For our analytic results, we assume no order crossing. We derive the cost function for a capacitated two-echelon inventory system with general transportation times under these policies. Our numerical examples show that the FCFS policy may outperform the MR policy, even though the latter has been shown to be better in the centralized setting. This suggests that in decentralized settings there is a need to focus on policies that prioritize customers when there is backlog. This focus is in contrast to the centralized settings, where inventory rationing policies that focus on prioritization when there is available inventory are effective. We therefore introduce and analyze the generalized multilevel rationing (GMR) priority policy. We compare the GMR policy with other policies and show that the GMR policy outperforms the three policies used in the centralized setting. We also compare the GMR policy with the myopic (T), longest queue first (LQF), and the optimal (when order crossing is allowed during the transportation time) policies. Our results show that when the uncertainty of the transportation times is low, the GMR policy outperforms the myopic (T) and LQF policies and that the gap between the optimal policy and the GMR policy is not high.
机译:我们考虑一个两级库存系统,该系统具有功能强大的集中式生产设施和几个配送中心(DC)。生产和运输时间都是随机分布的。需求根据独立的Poisson流程到达每个DC,如果DC缺货则积压。我们在不同的区议会允许不同的持有和积压成本。我们假设配送中心的库存使用一对一补货策略进行管理。本文的主要目的是研究一般运输时间对多级M / G / 1设置的控制。为了实现此目标,我们分析了几种分散式分配策略,包括先来先服务(FCFS),严格优先级(SP)和多级配给(MR)策略。对于我们的分析结果,我们假设没有订单交叉。在这些政策下,我们得出了具有一般运输时间的带容量的两级库存系统的成本函数。我们的数值示例表明,即使已证明在集中式环境下MRFS策略更好,但FCFS策略可能会优于MR策略。这表明在分散的环境中,需要重点关注在积压订单时优先考虑客户的策略。此重点与集中式设置相反,集中式设置在集中可用库存时优先考虑优先级的库存配给策略是有效的。因此,我们引入并分析了广义多级配给(GMR)优先级策略。我们将GMR政策与其他政策进行了比较,结果表明GMR政策优于集中式设置中使用的三个政策。我们还将GMR策略与近视(T),最长队列优先(LQF)和最佳(在运输时间内允许订单穿越时)策略进行比较。我们的结果表明,当运输时间的不确定性较低时,GMR策略的表现要优于近视(T)和LQF策略,并且最优策略和GMR策略之间的差距并不大。

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