Route optimization for warehouse order picking operations via vehicle routing and simulation

Order picking has been recognized as one of the most challenging activities in terms of time, labor, and cost for most warehouses. Order fulfillment has a definite time constraint that is predefined by the customer and any deficit in the process of order picking at the warehouse level will impact the entire supply chain. This paper addresses the problem of routing optimization for order picking in a warehouse to minimize the travel time and distance. In particular, we propose an easy-to-implement vehicle routing based approach in conjunction with the distance matrix for obtaining an optimal route for order picking, which is solved using the off-the-shelf solver Gurobi with the Julia programming language. The optimal route is then compared with the routes obtained by other traditional approaches such as S-shape, return, mid-point, and largest gap methods by means of simulation. Two order picking demand scenarios are considered: one with uniform pick locations throughout the warehouse and the other with differentiated pick locations. We show that the proposed vehicle routing based approach outperforms the S-shape, return, mid-point, largest gap methods by 36.55%, 44.89%, 46.64%, and 36.9 %, respectively, for scenario 1, and by 25.12%, 24.01%, 27.57%, and 26.77%, respectively, for scenario 2. The detailed discussion about the routing policy implications on management is also provided.