Slotting methodology using correlated improvement for a zone-based carton picking distribution system

This study presents slotting methodologies for a zone-based carton picking distribution system (DC). The study involves a slotting problem: assigning SKUs to slots in the zone-based carton picking DC in which we have predetermined the assignment of items into cartons (cartonization). First we present a mathematical formulation for solving the slotting problem. Due to the difficulty in solving large problems, we develop four two-phase heuristics for the slotting problem. One of the heuristics presented solves the slotting problem using a simulated annealing improvement heuristic based on correlated interchange (SA-C). Since the performance of the SA-C heuristic depends on the correlation of items in the same carton, we also develop a correlated carton list generation methodology with SKUs correlation. Promising computational results are shown using the data representative of a large DC.

► Solution for a dynamic slotting problem in a carton picking distribution center.
► Simulated annealing improvement heuristic based on correlated improvement.
► Correlated carton list generation methodology for sample data with SKU correlation.