A Stochastic Joint Replenishment Problem with Dissimilar Items.

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. [ABSTRACT FROM AUTHOR]