A Greedy Primal-Dual Type Heuristic to Select an Inventory Control Policy

Abstract

We propose a greedy primal-dual type heuristic to jointly optimize the selection of an inventory control policy and the allocation of shelf space in order to minimize the expected counting and replenishment costs, while accounting for space limitations. The problem is motivated by an application in the healthcare sector. It addresses the limitations in designing an inventory control system for hospitals stockrooms and the drawbacks of the common approach of using a single policy such as a two-bin Kanban or a Periodic Automatic Replenishment (PAR) system for all items. In the proposed approach, we not only choose policies to use available storage space more efficiently but also consider changing the policies or their parameters to use the space within a selected storage bin more efficiently. On numerical examples where a mathematical programming formulation can be solved in a reasonable amount of time, our experiments indicate that the proposed algorithm is very efficient.