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