Journal ArticleDOI
The adaptive approach for storage assignment by mining data of warehouse management system for distribution centres
TLDR
It turns out that DMSA outperforms random assignment as the number of put away products and the proportion ofPut away products with high turnover rates increase.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.read more
Citations
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References
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Book
Data Mining: Concepts and Techniques
TL;DR: This book presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects, and provides a comprehensive, practical look at the concepts and techniques you need to get the most out of real business data.
Proceedings ArticleDOI
Mining association rules between sets of items in large databases
TL;DR: An efficient algorithm is presented that generates all significant association rules between items in the database of customer transactions and incorporates buffer management and novel estimation and pruning techniques.
Journal ArticleDOI
Mining generalized association rules
TL;DR: A new interest-measure for rules which uses the information in the taxonomy is presented, and given a user-specified “minimum-interest-level”, this measure prunes a large number of redundant rules.
Journal ArticleDOI
Design and control of warehouse order picking: A literature review
TL;DR: In this paper, a literature overview on typical decision problems in design and control of manual order-picking processes is given, focusing on optimal (internal) layout design, storage assignment methods, routing methods, order batching and zoning.
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