An Effective Lateral Transhipment Model for A Multi-Location Inventory Setting to Minimize

Abstract

Managing inventory levels to ensure on-shelf availability of products is a challenge that retailers face on a daily basis. Even though it is desirable to have additional inventory to ensure the availability of products, it increases the inventory holding cost. Hence, retailers use lateral transhipment as a method to redistribute inventory from a location which has excess inventory to another outlet which faces / will face stockouts. This paper proposes a mathematical model to minimize the total cost through proactive lateral transhipment while reducing the stockouts, significantly. A multi-item, multi-location inventory system was considered, and a cost minimization model was developed based on the tradeoff between the potential gain and the transhipment cost. The model was implemented using Python programming language and validated using a real-world data set from one of the leading supermarket chains. The results from the model have shown that it can reduce the total cost and stockout occurrences significantly.