Multi‐Item Grouping Algorithm Yielding Near‐Optimal Logistics Cost
提出一种多物品分组补货的启发式算法，在无法穷举所有分组的情况下最小化总物流成本，并报告了在零售企业517个库存物品上的应用效果。
ABSTRACT This article describes an algorithm used to formulate an inbound consolidation strategy when multi‐items are replenished in groups and when total logistics cost is to be minimized. The importance of this algorithm is threefold (1) no optimal procedure exists for grouping multi‐items when minimizing total logistics cost, (2) a complete enumeration of all possible groups (from which the optimal grouping set can be identified) is impractical due to the combinatorial nature of the grouping problem, and (3) no other heuristics have been developed that adequately reflect shipping cost in the analysis like this one does. We report the experience of using this algorithm to group and reorder 75 selected ensembles containing a total of 517 inventory items of a retail merchandising firm.