Supply chain forecasting model using computational intelligence techniques

Nowadays, supply chain is more complex with the advance of technology. One of the important tasks in supply chain management is product demand forecasting as it provide initial figure for various plan to work on, for example, production, inventory, personnel. The complexity of supply chain makes the...

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Main Author:	Laosiritaworn,W.S.
Format:	Article
Published:	Chiang Mai University 2015
Subjects:	Multidisciplinary
Online Access:	http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84872203103&origin=inward http://cmuir.cmu.ac.th/handle/6653943832/39006
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Institution:	Chiang Mai University

id	th-cmuir.6653943832-39006
record_format	dspace
spelling	th-cmuir.6653943832-390062015-06-16T08:01:07Z Supply chain forecasting model using computational intelligence techniques Laosiritaworn,W.S. Multidisciplinary Nowadays, supply chain is more complex with the advance of technology. One of the important tasks in supply chain management is product demand forecasting as it provide initial figure for various plan to work on, for example, production, inventory, personnel. The complexity of supply chain makes the traditional techniques become less appropriate. This paper propose an application of Artificial neural network (ANN) and Support vector regression (SVR) to forecast product demand. A case study of an arm coil of a hard disk from a hard disk drive part manufacturing was used to demonstrate the proposed techniques. 2015-06-16T08:01:07Z 2015-06-16T08:01:07Z 2011-08-01 Article 16851994 2-s2.0-84872203103 http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84872203103&origin=inward http://cmuir.cmu.ac.th/handle/6653943832/39006 Chiang Mai University
institution	Chiang Mai University
building	Chiang Mai University Library
country	Thailand
collection	CMU Intellectual Repository
topic	Multidisciplinary
spellingShingle	Multidisciplinary Laosiritaworn,W.S. Supply chain forecasting model using computational intelligence techniques
description	Nowadays, supply chain is more complex with the advance of technology. One of the important tasks in supply chain management is product demand forecasting as it provide initial figure for various plan to work on, for example, production, inventory, personnel. The complexity of supply chain makes the traditional techniques become less appropriate. This paper propose an application of Artificial neural network (ANN) and Support vector regression (SVR) to forecast product demand. A case study of an arm coil of a hard disk from a hard disk drive part manufacturing was used to demonstrate the proposed techniques.
format	Article
author	Laosiritaworn,W.S.
author_facet	Laosiritaworn,W.S.
author_sort	Laosiritaworn,W.S.
title	Supply chain forecasting model using computational intelligence techniques
title_short	Supply chain forecasting model using computational intelligence techniques
title_full	Supply chain forecasting model using computational intelligence techniques
title_fullStr	Supply chain forecasting model using computational intelligence techniques
title_full_unstemmed	Supply chain forecasting model using computational intelligence techniques
title_sort	supply chain forecasting model using computational intelligence techniques
publisher	Chiang Mai University
publishDate	2015
url	http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84872203103&origin=inward http://cmuir.cmu.ac.th/handle/6653943832/39006
_version_	1681421576407351296

Supply chain forecasting model using computational intelligence techniques

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