Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/4450
Title: Association rule based approach for improving operation efficiency in a randomized warehouse
Authors: Chan, Hau Ling
Pang, Anthony
Li, Ka Wing
Subjects: Warehousing operations
Storage location assignment problem
Order picking
Data mining
Association rules
Issue Date: 2011
Publisher: IEOM Research Solutions Pty Ltd.
Source: 2nd International Conference on Industrial Engineering and Operations Management (IEOM 2011) : January 22-24, 2011, Kuala Lumpur, Malaysia : proceedings, p. 704-710.
Abstract: Data mining has long been used in relationship extraction from large amount of data for a wide range of applications such as consumer behavior analysis in marketing. Some research studies have also extended the usage of this concept in warehousing operations management to determine the order picking policy by batching the orders to minimize the picking distance. Yet, not many research studies have considered the application of the data mining approach on storage location assignment decision to minimize the manual effort on put-away execution which is also a significant factor to the constituent of warehousing operation cost. We present a data mining approach for the storage location assignment problem in a randomized warehouse using association rules extraction algorithm. Result of the preliminary experimental study shows that our proposed storage location assignment algorithm is efficient in determining the correlated products storage location that minimizes the total travel distances of both order picking and put-away operations for a randomized less-than-unit-load warehouse.
Rights: © 2011 IEOM Research Solutions Pty Ltd. Posted by permission of the publisher.
Type: Conference Paper
URI: http://hdl.handle.net/10397/4450
ISBN: 978-0-9808251-0-7
Appears in Collections:LMS Conference Papers & Presentations

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