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

机译:基于离散排队模型的基础库存控制生产库存系统分析

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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,我们关注的是一个由生产工厂和一个仓库组成的生产库存(PI)系统,该系统面临着来自客户的大量需求。我们提出了离散时间排队模型,该模型可用于评估给定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,我们确定了仓库中的最佳基本库存水平,该水平将使单位存货的单位时间的长期总预期成本,与积压队列中服务订单相关的积压成本最小化。在替代模型中,我们根据仓库的缺货概率将缺货作为服务级别约束。在这些模型中,我们假设客户不会从系统中脱颖而出。在本文中,将到达仓库的客户订单假定为Poisson过程。制造工厂的服务过程具有离散的随机变量分布。提供了一些示例来验证模型并说明其各种功能。

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