A Stochastic Joint Replenishment Problem with Dissimilar Items
研究了运输容量有限且物品大小不同的随机联合补货问题，提出了一种数据结构和算法，并开发了多种启发式策略，其中(U,S)策略在物品差异大时表现稳健高效。
ABSTRACT The classical stochastic joint replenishment problem (SJRP) often assumes uncapacitated batch size, and identical items. However, real problems encountered relate to the truck , or the container which has limited capacity. When the shipping capacity is limited, and the items are dissimilar in size, the problem becomes more challenging. By defining a class of order‐up‐to policies, we formulate the SJRP of this kind as a combinatorial optimization problem. To solve the problem, a data structure and an algorithm are developed. Based on the algorithm, we also suggest several heuristics including the ( U , S ) policy—a generalization of the well‐known ( Q , S ) policy for dissimilar items. The numerical study shows the ( U , S ) policy is robust and efficient. It performs well, especially when the items become more dissimilar, in terms of shipping size and inventory velocity.