Dynamic batch picking is characterized by combining product demand from multiple customer orders into one pick tour where new orders are continuously received. Using modern order-picking aids, updated picking instructions can be included in the current pick tours which allows pickers to be re-routed to pick for new orders even when they already started a pick tour. We develop a mathematical model for dynamic batch picking that minimizes the order throughput time of incoming customer orders. In case of new order arrivals, we can quickly re-optimize the model and determine new updated pick tours. This allows for short order throughput times and ensures that warehouse companies can set their order cut-off times as late as possible while still guaranteeing that orders can be delivered next day or in some cases even the same day
