Purchase Planning for Minimum Assortment Goods Given the Uncertainty of Demand

D. Andreev, A. Khutoretsky
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Abstract

Some retailers (e.g. pharmacies) are responsible for satisfying the demand for the minimum range of goods, which are generally unprofitable. With respect to such goods, the enterprise seeks to satisfy uncertain demand rather than to make profit. We assume that: (a) the vector of demand for goods of the minimum assortment in the planning period lies “between” the demand vectors of several previous periods (is a convex linear combination of these vectors); (b) the smaller the maximum unsatisfied demand (by product groups and possible vectors of demand), the greater is the reliability of meeting the demand. Under these assumptions, we address the problem of allocating a limited procurement budget among commodity groups to meet uncertain demand most reliably. The article shows that this problem is equivalent to finding an optimal strategy by Wald’s criterion in some game with nature and can be reduced to a linear programming problem. Using the problem features, we propose a fast (having quadratic complexity) algorithm for constructing an optimal procurement plan. The model can be used when planning the minimum assortment goods procurement in order to maximize the meeting demand reliability, achievable within the allocated budget. As far as we know, such a formulation of the problem has not been studied in the previous literature.
考虑需求不确定性的最小分类商品采购计划
一些零售商(如药店)负责满足对最低限度商品的需求,这通常是无利可图的。对于这类商品,企业追求的是满足不确定的需求,而不是获取利润。我们假设:(a)规划期内最小品种商品的需求向量“介于”前几个时期的需求向量之间(是这些向量的凸线性组合);(b)最大未满足需求(按产品组和可能的需求向量计算)越小,满足需求的可靠性越高。在这些假设下,我们解决了在商品组之间分配有限采购预算以最可靠地满足不确定需求的问题。本文表明,该问题等价于用瓦尔德准则寻找具有自然性质的对策的最优策略,可以简化为线性规划问题。利用问题特征,提出了一种快速(具有二次复杂度)的最优采购计划构建算法。该模型可用于规划最小品种的商品采购,以最大限度地满足需求的可靠性,在分配的预算范围内实现。据我们所知,以前的文献中还没有研究过这种问题的表述。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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