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Analysis of base-stock controlled production-inventory system using discrete-time queueing models

机译:采用离散时间排队模型分析基础股票控制生产库存系统

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In this paper, we concern ourselves with a production-inventory (PI) system consisting of a manufacturing plant and one warehouse which faces a stream of demands from customers. We present discrete-time queueing models which can be used for evaluating the performance of a given production-inventory system which processes customer orders with service times that are discrete random variables. This analysis can be embedded in an optimization model which can be used for designing efficient inventory policies. In particular we determine the optimal base-stock level at the warehouse that minimizes the long term total expected cost per unit time of carrying inventory, backorder cost associated with serving orders in the backlog queue. In an alternate model, we impose stock out as a service level constraint in terms of probability of stock out at the warehouse. In these models we assume that customers do not balk from the system. In this paper, the customers orders arriving at warehouse are assumed to Poisson process; the service process at the manufacturing plant has the distribution of a discrete random variable. Several examples are presented to validate the model and to illustrate its various features.
机译:在本文中,我们涉及由生产工厂和一个仓库组成的生产库存(PI)系统,该仓库面向客户需求流。我们呈现离散时间排队模型,可用于评估给定的生产库存系统的性能,该系统处理具有离散随机变量的服务时间的客户订单。该分析可以嵌入在优化模型中,该模型可用于设计有效的库存策略。特别是我们确定仓库中的最佳基础股票水平,最小化每单位携带库存的长期总预期成本,与在Backlog队列中服务订单相关的延期交货成本。在替代模型中,我们在仓库中的库存概率方面将库存作为服务水平约束。在这些模型中,我们假设客户不会从系统中击败。在本文中,假设仓库的客户订单被认为是泊松过程;制造工厂的服务过程具有离散随机变量的分布。提出了几个示例以验证模型并说明其各种功能。

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