The adaptive approach for storage assignment by mining data of warehouse management system for distribution centres

Authors:
David Ming-Huang Chiang;Chia-Ping Lin;Mu-Chen Chen
Affiliations:
Graduate Institute of Business Administration, National Taiwan University, Taipei, Taiwan;Graduate Institute of Business Administration, National Taiwan University, Taipei, Taiwan;Institute of Traffic and Transportation, National Chiao Tung University, Taipei, Taiwan
Venue:
Enterprise Information Systems
Year:
2011

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Abstract

Among distribution centre operations, order picking has been reported to be the most labour-intensive activity. Sophisticated storage assignment policies adopted to reduce the travel distance of order picking have been explored in the literature. Unfortunately, previous research has been devoted to locating entire products from scratch. Instead, this study intends to propose an adaptive approach, a Data Mining-based Storage Assignment approach (DMSA), to find the optimal storage assignment for newly delivered products that need to be put away when there is vacant shelf space in a distribution centre. In the DMSA, a new association index (AIX) is developed to evaluate the fitness between the put away products and the unassigned storage locations by applying association rule mining. With AIX, the storage location assignment problem (SLAP) can be formulated and solved as a binary integer programming. To evaluate the performance of DMSA, a real-world order database of a distribution centre is obtained and used to compare the results from DMSA with a random assignment approach. It turns out that DMSA outperforms random assignment as the number of put away products and the proportion of put away products with high turnover rates increase.