Joint storage assignment and picker routing optimization in warehouses

Storage assignment and picker routing are critical factors influencing warehouse operational efficiency, with inherent interdependence between them. However, existing studies rarely investigate their coupling relationships, instead adopting a sequential decision-making approach, optimizing one while keeping the other fixed. Moreover, most prior studies assume an initially empty warehouse, neglecting the practical scenario where certain storage locations are occupied during previous picking operations. This paper establishes an integrated optimization model for storage assignment and picker routing that incorporates storage occupancy constraints, aiming to minimize the total processing time required to complete given orders. The problem is proven to be NP-hard, and a variable neighborhood search (VNS) algorithm is proposed. Numerical experiments demonstrate that the algorithm quickly obtains optimal solutions for small-scale instances and near-optimal solutions for large-scale instances within a short computation time. Compared with the sequential approach, the integrated approach reduces the total processing time by approximately 12.6%. Furthermore, in contrast to methods in the literature that ignore storage occupancy constraints, the proposed algorithm can reduce the total processing time by up to 7.8%. Finally, a real-world case study is used to validate the superiority of the model and algorithm.