Multicriteria Optimization in a Typical Multi-Isle Warehouse with Multiple Racks

Abstract

This paper considers two common problems frequently found in warehouses: slotting and picking. The former refers to the best arrangement of items in the warehouse, while the latter concerns the definition of the best route to pick up the selected objects. In most industrial practice, the implementation of picking and slotting optimization techniques uses information based on historical data that, in most cases, would fail to work because of many factors affecting daily operations in the warehouse. Simulation models have been employed to build virtual scenarios in order to predict the outcomes of a specific operational decision. Simulation models also fail because collected data is not fully reliable. In order to overcome those problems, this paper proposes the use of a hybrid simulation and optimization approach in which real-time data is incorporated thanks to radio-frequency identification (RFID) technology. Operational decisions are hence made in real-time. The approach is validated using real data from a pharmaceutical manufacturer.