In order to respond to the recent increasing e-commerce demand more quickly and accurately, many logistics companies operate fulfillment centers which pick the goods for customers’ orders from shelves and deliver the boxes with the goods directly to...
In order to respond to the recent increasing e-commerce demand more quickly and accurately, many logistics companies operate fulfillment centers which pick the goods for customers’ orders from shelves and deliver the boxes with the goods directly to customers. In this paper, we deal with the order selection problem for a unique zone-picking system in a fulfillment center which prioritizes the orders to allocate to the system in real time. Unlike other order selection problems that assume the picking rates of workers are constant and known, our problem considers that the actual picking rates can vary from person to person and change over time. We propose a new order selection method and compare it to three different existing methods by using a simulation model that mimics a real fulfillment center. The methods are tested under a stationary state in that the workers’ work speeds are fixed and also under two different non-stationary states in that the workers’ work speeds change over time. The proposed order selection method provides lower makespans, lower flow times, and higher throughputs not only in the stationary state but also in the non-stationary states when compared to those of other existing methods.