Distribution Center Analytics
Association Rule Mining
Data mining analyzes significantly large datasets containing information about the orders received by DC's to discover the relationships between SKU's and determine their storage location.
PUBLICATIONS
Using association rule mining algorithms to improve the order picking operations in distribution centers
In this paper, the association rules mining algorithm is applied to the distribution center’s order picking processes. The framework creates itemsets of stock-keeping units (SKU) frequently found in the same order and positions an item near the rest of the members of the family to reduce the order picking time. This paper is under review.
Storage location assignment heuristics based on slot selection and frequent itemset grouping for large distribution centers
This working paper considers heuristic approaches to assign stock keeping units (SKU) to individual slots in the distribution center. Two novel strategies are proposed for slot selection and frequent itemset grouping. The former is used to find the most suitable slot for a single SKU, while the latter is for sequencing SKUs in the appropriate order.