The impact of variation on the performance of order picking strategies in daily warehouse operationss

An order-picking strategy is traditionally selected in the design phase of a warehouse, and its planning is based on average historical data and assumptions on the development of the business. Daily order-picking operations, however, are subject to various types of variability that arise both from external, i.e., varying demand, and internal, i.e., varying picking parameters, of the order-picking area. Consequently, the implemented order-picking strategy in picking operations (typically remaining unchanged) may no longer be the most efficient anymore when variations occur. We investigate the impact of variability on multiple manual order-picking strategies using simulation. We answer which strategy suits best to which operational situation and if the selection changes when multiple performance measures are considered.

Katja Linda Thamm joined Kühne Logistics University as PhD Candidate in July 2019 supervised by Prof. Dr. Sandra Transchel and Prof. Dr. Henrik Leopold. In her research, Katja combines actual observations in reality with operations management and machine learning, specifically in manual order picking warehouse operations. Katja has professional experience since 2007 in SCM and logistics, focusing on optimization and digitalization. Since 2017 she works as a consultant with Retail Capital Partners AG, who is also project sponsor. She received her MSc in Global Logistics at KLU in 2012, with being KLU Master’s Thesis Award winner. In 2007, she received a Diploma in Business Administration, specialized in Forwarding, Transport and Logistics at DHBW Mannheim. Katja is now in her second year of the PhD program after maternity leave.