This research addresses operational inefficiencies in a real-world fulfilment centre by focusing optimising the order picking process. The primary objective is to develop a solution that aligns the company’s operations with the best practices in the warehousing industry by optimising both order batching and picker routing.
The problem is formulated as a Two-Stage Order Picking Problem with Batching and mixed-layout Ultra-Narrow Aisles (TS-OPPB-UNA), a unique challenge not widely addressed in existing literature. A two-stage metaheuristic solution framework is proposed, where in the first stage, efficient batches are created by grouping customer orders. The second stage calculate near-optimal routes for each batch, specifically designed to handle the warehouse’s mixed-layout of standard and ultra-narrow aisles.
The performance of the developed algorithm is extensively tested and benchmarked against a mathematical (MILP) model and the company’s current manual process. It was shown that the proposed solution can reduce total travel distance by more than 50%. The key conclusion is that to achieve these significant efficiency gains, the algorithmic solution must be combined with digital picking technologies, such as handheld scanners, to make sure that pickers adhere to the optimised routes.