Human-and-cost-centric storage assignment optimization in picker-to-parts warehouses

Warehouses are key for supply chain efficiency and company success. Over the past decade, warehouse operations have become more complex due to small-quantity orders with volatile demand patterns and the need for fast and error-free deliveries. In line with these developments, order picking is among the most critical tasks in warehouses, as it directly impacts the speed, availability and accuracy of the order. Although we see an increasing use of assistive and automation technology in order picking, manual tasks are still prevalent, and warehouse employment increases constantly. The high amount of manual work in order picking poses a risk environment for workers to develop injuries, which is why a research stream that focuses on the joint optimization of operational performance indicators and human well-being has emerged. This work contributes to this research area by developing an integrated storage assignment model that considers the vertical and horizontal dimension as well as the simultaneous minimization of the total order processing time and the minimization of the order picker’s total physical strain. Based on the results of numerical experiments, which are inspired by practical cases, we propose improved storage assignment policies for the case that order pickers follow the return or traversal routing strategy. This work contributes to further developing the research stream of human-centered warehousing and highlights implications for warehouse managers to improve working conditions with simultaneous consideration of performance optimization.