Optimization of warehouse picking to maximize the picked orders considering practical aspects

Majority of previous studies on optimization of warehouse order picking lack real-world application and overlook complexities such as varying items' weight, workload balance, and heterogeneous pickers. To address these issues, in this study, mathematical programming models are developed based on two approaches to assign orders to pickers and determine pickers' routes in a North American consumer goods warehouse. Both approaches maximize the number of picked orders. However, in the simultaneous modelling approach, decisions are made in one model, while in the sequential modelling approach, first routing decisions then order assignment decisions are made. The sequential modelling approach compared with the simultaneous one yields better results in a shorter time. For the considered warehouse, the results suggest that the warehouse may not be able to handle more than 700 orders per shift without expanding its workforce. Furthermore, adding one picker results in an approximate 2% increase in picked orders. Additionally, balancing pickers' workload is more effective when there are fewer than 600 orders available for picking per shift, because with a higher number of orders, pickers remain busy throughout the entire shift. The proposed mathematical modelling approaches enable warehouse managers and staff to process more orders with available resources (equipment, time, staff) and make better decisions using available data.