Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/55554
Title: An intelligent fuzzy-based storage assignment system for packaged food warehousing
Authors: Hui, YYY
Choy, KL 
Ho, GTS
Lam, CHY
Lee, CKH
Cheng, SWY
Issue Date: 2015
Publisher: Portland State University
Source: Portland International Conference on Management of Engineering and Technology, PICMET 2015, 2-6 August 2015, 7273209, p. 1869-1878 How to cite?
Abstract: In the packaged food industry, fast cargo receiving, reliable storage and accurate order picking in warehouses within short period of time are critical for achieving customer satisfaction. Food easily deteriorates when unloaded packaged food is exposed in an open area, waiting for inbound and packing operations, according to customer orders. In addition, the risk of damaging the packaging of food is higher when the food is frequently transported by forklift trucks during order picking. This highlights the need to provide decision support in warehouse zoning and storage assignment for preventing the above risks occurring. This paper proposes a tri-modular intelligent fuzzy-based storage assignment system, integrating fuzzy logic and association rules mining techniques, to reduce the order-picking and cargo exposure time, as well as the transport frequency and distance. The fuzzy zoning module is used to allocate different types of packaged food to various warehouse zones based on their particular characteristics. The location assignment module reveals hidden relationships in the sales of products, in turns suggesting which products should be placed together in the same zone. A case study is carried out to examine the intelligent system.
URI: http://hdl.handle.net/10397/55554
ISBN: 9781890843328
DOI: 10.1109/PICMET.2015.7273209
Appears in Collections:Conference Paper

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

1
Last Week
0
Last month
Citations as of Dec 2, 2017

Page view(s)

33
Last Week
4
Last month
Checked on Dec 4, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.