Abstract

The Periodic Inventory control policy (R, S) is one of the most employed and studied strategies by practitioners and researchers in a variety of contexts. In the last two decades, Inventory Location literature has been focused on the integration of inventory control issues into facility location models for addressing Supply Chain Network Design problems. However, most of Inventory Location related research mainly focus on other inventory control policies, such as the continuous review policy (s, Q), denoting a significant unfilled research gap. Thus, this research proposes and formulates an Inventory Location Problem under a Periodic Inventory control policy (R, S) as a novel Mixed Integer, Nonlinear, Nonconvex Programming model to deal with Supply Chain Network Design. In addition, and according to the high problem complexity, an efficient and effective solution approach based on the Generalized Benders decomposition is proposed and implemented to solve the proposed formulation. In a wide variety of synthetic sized tested instances, the algorithm reached global optimality (i.e., zero duality gap), mostly in competitive times" has been replaced with "80% of the instances (768 out of 960) were solved in less than 30 s. The proposed formulation, along with the solution approach, provides a useful decision support methodology for designing the Supply Chain Network where the inventory control policy (R, S) is employed. Based on this research, significant research and managerial insights are presented and discussed.