口吃泊松需求过程下最优(s, s)和(R, nQ)策略的注释

C. Larsen
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引用次数: 0

摘要

本文提出了一种新的高效算法,用于寻找具有连续评审且需求遵循断断续续泊松过程(复合元素呈几何分布)的库存系统的最优(s, s)补货策略。我们还推导出如果使用最佳(R, nQ)策略而不是最优(s, s)策略,成本相对增加的三个上界。其中一个上限(其中最宽松的上限)可以表示为几何分布的方差与均值之比与经济订货量的分数。当这些上界很紧时,我们用数值方法来研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A note on optimal (s, S) and (R, nQ) policies under a stuttering Poisson demand process
In this note, a new efficient algorithm is proposed to find an optimal (s, S) replenishment policy for inventory systems with continuous reviews and where the demand follows a stuttering Poisson process (the compound element is geometrically distributed). We also derive three upper bounds for the relative increase in cost if one uses the best (R, nQ) policy instead of the optimal (s, S) policy. One of these upper bounds (the most loose of those) can be expressed as the fraction of the variance-to-mean ratio of the geometric distribution and the economic order quantity. We explore numerically when these upper bounds are tight.
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