Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/66219
Title: A fuzzy association rule mining framework for variables selection concerning the storage time of packaged food
Authors: Hui, YYY
Choy, KL 
Ho, GTS
Lam, HY
Keywords: Decision support
Fuzzy association rule mining
Packaged food
Storage time
Variables selection
Issue Date: 2016
Publisher: Institute of Electrical and Electronics Engineers Inc.
Source: 2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016, 2016, 7737751, p. 671-677 How to cite?
Abstract: The growth in the packaged food industry has created pressure on the packaged food warehouse to enhance the order-picking efficiency. The decision support system (DSS) for stock keeping units (SKUs) allocation thus has to make quality decisions for shortening the order-picking time. In order to improve the decision making ability of the DSS, the determinant factors of the major input variable -The storage time of SKUs, have to be identified. Given the imprecise nature of the potential determinant factors, a fuzzy association rule mining (FARM) framework is proposed in this study. It applies the FARM technique to identify and evaluate the factors and patterns concerning the storage time of SKUs in packaged food warehouses. The framework was tested through a case study, and the results showed that the framework is able to identify the most relevant input variables in regard to the storage time and can describe the relationships between them specifically.
Description: 2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016, Vancouver, Canada, 24-29 July 2016
URI: http://hdl.handle.net/10397/66219
ISBN: 9781509006250
DOI: 10.1109/FUZZ-IEEE.2016.7737751
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