International Journal of Computational Intelligence Systems

Volume 7, Issue sup2, July 2014, Pages 85 - 92

Demand forecasting procedure for short life-cycle products with an actual food processing enterprise

Authors
Rie Gaku
Corresponding Author
Rie Gaku
Available Online 9 January 2017.
DOI
https://doi.org/10.1080/18756891.2014.947121How to use a DOI?
Keywords
Demand Forecasting, Data Mining, Short Life-cycle, Convenience store
Abstract
A procedure of demand forecasting using data mining techniques is proposed to forecast the sales amount of new short life-cycle products for an actual food processing enterprise. The enterprise annually produces 100∼150 kinds of new items with short life-cycle between one week and three months to supply 260 convenience stores in the region of jurisdiction. Based on the previous delivery data in the first selling week, sales amount in the second, and the third selling weeks can be forecasted for their new products. Especially, some effective association rules about hot items and cold items are obtained by using data mining technologies for new short life-cycle products.
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This is an open access article distributed under the CC BY-NC license.

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
7 - 100
Pages
85 - 92
Publication Date
2017/01
ISSN
1875-6883
DOI
https://doi.org/10.1080/18756891.2014.947121How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - JOUR
AU  - Rie Gaku
PY  - 2017
DA  - 2017/01
TI  - Demand forecasting procedure for short life-cycle products with an actual food processing enterprise
JO  - International Journal of Computational Intelligence Systems
SP  - 85
EP  - 92
VL  - 7
IS  - sup2
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2014.947121
DO  - https://doi.org/10.1080/18756891.2014.947121
ID  - Gaku2017
ER  -