Warehouse Analytics: Order Consolidation and Pallet Loading

Speaker: Dr. Samir Elhedhli (Waterloo)

Abstract: Inspired by an industrial project with a global warehouse logistics management company and based on real data, we model and solve two practical, yet challenging, problems in warehouse management. In the first one, we study the order fulfillment process in an e-commerce warehouse. Based on data and without prior knowledge of layout and process flow, we analyze the picking, order fulfillment, and order consolidation operations in warehouse management. We then define what we call the Order Consolidation Problem (OCP) to optimize tote sequencing and order fulfillment. The OCP is a new problem in warehouse management and parallel machine scheduling. We provide a mathematical formulation and devise two solution methodologies. In the second, we study the Pallet Loading Problem (PLP) in retail distribution. The PLP is an extension of three-dimension bin packing that requires additional constraints such as item support, pallet stability, load bearing, machine packability, family groupings and isle friendliness. We propose a novel formulation and a column generation approach where the pricing subproblem is a two-dimensional layer generation problem. Layers are highly desirable in practice as they are easily packable and can accommodate most practical constraints. The proposed methodology is capable of solving large industry-size instances within the industry standard of 2 minutes.