Inventory Positioning in Supply Chain Network: A Service-Oriented Approach

Abstract

This study develops a mixed-integer linear programming model based on a guaranteed service approach for an inventory positioning problem in a supply chain under the base stock inventory policy. Our proposed model aims to determine appropriate inventory positions and amounts and the optimal service level for the supply chain to minimize the total cost of safety inventory holding and shortage. Two demand scenarios, based on normal and empirical distributions, are investigated. An extensive numerical experiment is conducted to illustrate the applicability and effectiveness of our model, especially under empirical distribution. The experiment features a practical network structure and demand data from an industrial user. Moreover, to further validate the experimental results from the mathematical model, they are compared with the result from a simulation model, which is constructed to imitate the operations of the supply chain. The comparison result indicates that the model solution under the empirical demand distribution is close to the simulation regarding the difference in the total cost (less than 1%). This solution significantly outperforms the model solution under the normal demand, which results in a significant difference in total cost (more than 25%) compared to the simulation.

Keywords

• Base stock policy
• empirical demand
• guaranteed service approach
• inventory positioning
• mixed-integer linear programming
• multi-echelon inventory system