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首页> 外文期刊>Management science: Journal of the Institute of Management Sciences >A Threshold Inventory Rationing Policy for Service-Differentiated Demand Classes
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A Threshold Inventory Rationing Policy for Service-Differentiated Demand Classes

机译:服务差异化需求类别的阈值库存配给策略

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Motivated by a study of the logistics systems used to manage consumable service parts for the U. S. military, we consider a static threshold-based rationing policy that is useful when pooling inventory across two demand classes characterized by different arrival rates and shortage (stockout and delay) costs. The scheme operates as a (Q, r) policy with the following feature. Demands from both classes are filled on a first-come-first-serve basis as long as on-hand inventory lies above a threshold level K. Once on-hand inventory falls below this level, low-priority (i.e. , low shortage cost) demand is backordered while high-priority demand continues to be filled. We analyze this static policy first under the assumption that backorders are filled according to a special threshold clearing mechanism. Structural results for the key performance measures are established to enable an efficient solution algorithm for computing stock control and rationing parameters (i.e. , Q, r, and K). Numerical results confirm that the solution under this special threshold clearing mechanism closely approximates that of the priority clearing policy. We next highlight conditions where our policy offers significant savings over traditional "round-up" and "separate stock" policies encountered in the military and elsewhere. Finally, we develop a lower bound on the cost of the optimal rationing policy. Numerical results show that the performance gap between our static threshold policy and the optimal policy is small in environments typical of the military and high-technology industries.
机译:基于对用于管理美军消耗品维修的后勤系统的研究的动机,我们考虑了一种基于阈值的静态定量配给策略,该策略在将具有不同到达率和短缺(缺货和延迟)特征的两个需求类别中汇总库存时非常有用费用。该方案用作具有以下功能的(Q,r)策略。只要现有库存高于阈值水平K,就按照先到先得的原则满足这两个类别的需求。一旦现有库存下降到该水平以下,则低优先级(即低短缺成本)需求被补货,而高优先级需求继续得到满足。我们首先假设根据特殊的阈值清算机制来补货,然后再分析此静态策略。建立了关键绩效指标的结构结果,以实现用于计算库存控制和配给参数(即Q,r和K)的有效解决方案算法。数值结果证实,在这种特殊的阈值清除机制下的解决方案与优先级清除策略的解决方案非常接近。接下来,我们将重点介绍一些条件,在这些条件下,我们的政策比在军方和其他地方遇到的传统“全面”政策和“独立存货”政策要节省得多。最后,我们确定了最佳配给政策成本的下限。数值结果表明,在军事和高科技行业典型的环境中,我们的静态阈值策略和最优策略之间的性能差距很小。

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