dr. M. (Mengfei) Yu

This thesis studies order picking in warehouses. Order picking, the process of retrieval products from their storage locations to fill customer orders, is regarded as the most critical operation in a warehouse. Using stochastic modelling, we develop a model to estimate order picking system performance on various design alternatives and operating policies. The model is fast, flexible, and sufficiently accurate for practical purposes. The thesis introduces a concept of Dynamic Storage. In a Dynamic Storage System (DSS), orders are picked in batches and only those products needed for the current pick batch are retrieved from a reserve area and are stored in the pick area, just in time. Through analytical and simulation models, we demonstrate a DSS can substantially improve order throughput and reduce labour cost simultaneously over conventional order picking systems, where all the products required during a pick shift are stored in the pick area. The thesis also studies an internal distribution process at a flower auction company. Based on simulation and optimization models, we propose ways to reduce congestion and improve order lead time.