Generating In-Shelf Product Layout in Warehouse Using MIQCPs

Recently, the supply of warehouses has been increasing due to the development of e-commerce (EC) via the Internet. Among warehouse operations, picking is the most time-consuming. Currently, product placement is determined empirically, but there is a need to improve the placement in order to make the picking process more efficient. In this paper, we propose a method to generate product placement in a shelf by mathematical optimization. Products are divided into two groups as a product allocation problem, since the products are stored on two shelves facing each other. Then, the placement and volume of the products are optimized by solving mixed integer quadratically constrained problems such as placing heavy products on the lower shelves and separating similar products. We have conducted layout optimization experiments using real-world logistic data and discuss the effectiveness of the proposed method.