Routing order pickers in warehouses considering congestion and aisle width

Abstract

Due to the importance of routing order pickers, there has been extensive research in the area of routing to warehouses. However, there are still some prominent factors that should receive more attention, as they may lead to unsatisfactory services and considerable operational costs if ignored. In real-world applications, warehouse con guration, width of aisle, and controlling the vehicle congestion in the aisles greatly in uence the efficiency of the routing process. Therefore, this paper proposes a mixed-integer programming model, which aims to minimize maximum delivery time by nding the shortest pickup and delivery routes for all goods with all vehicles. Since the problem is NP-hard, a Simulated Annealing (SA) metaheuristic approach is designed to solve the model with large-size problems. This research contributes to the picker routing literature by considering dynamic congestion, narrow and wide aisles, and pickup times and proposing a metaheuristic algorithm. The validity and efficiency of our proposed model are proven by solving some various generated benchmark problems. In summary, the developed route planning mathematical model works e ectively for any two-dimensional rectangular layout and the collision prevention constraints are incorporated in the mathematical model.