A decision making model for vendor-buyer inventory systems

Wee, HM; Lu, J; Zhang, G; Chiao, HE; Gao, Y

A decision making model for vendor-buyer inventory systems

Wee, HM Lu, J

Zhang, G

Chiao, HE Gao, Y

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Publication Type:: Conference Proceeding
Citation:: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2009, 5908 LNAI pp. 336 - 343
Issue Date:: 2009-12-01

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Field	Value	Language
dc.contributor.author	Wee, HM	en_US
dc.contributor.author	Lu, J https://orcid.org/0000-0003-0690-4732	en_US
dc.contributor.author	Zhang, G https://orcid.org/0000-0003-3960-0583	en_US
dc.contributor.author	Chiao, HE	en_US
dc.contributor.author	Gao, Y	en_US
dc.date.issued	2009-12-01	en_US
dc.identifier.citation	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2009, 5908 LNAI pp. 336 - 343	en_US
dc.identifier.isbn	3642106455	en_US
dc.identifier.isbn	9783642106453	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.uri	http://hdl.handle.net/10453/10893
dc.description.abstract	In a vendor-buyer supply chain, the buyer's economic order quantity and the vendor's optimal number of deliveries are derived either independently or collaboratively. In this paper, we establish a two-stage vendor-buyer inventory system decision model by using bi-level decision making approach. The experimental result shows that the proposed bi-level decision model can effectively handle two-stage vendor-buyer inventory problems and obtain better results than the existing methods. © 2009 Springer-Verlag Berlin Heidelberg.	en_US
dc.relation.ispartof	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en_US
dc.relation.isbasedon	10.1007/978-3-642-10646-0_41	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	A decision making model for vendor-buyer inventory systems	en_US
dc.type	Conference Proceeding
utslib.citation.volume	5908 LNAI	en_US
utslib.for	080108 Neural, Evolutionary and Fuzzy Computation	en_US
utslib.for	080105 Expert Systems	en_US
utslib.for	080605 Decision Support and Group Support Systems	en_US
dc.location.activity	Delhi, India	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	5908 LNAI	en_US

Abstract:

In a vendor-buyer supply chain, the buyer's economic order quantity and the vendor's optimal number of deliveries are derived either independently or collaboratively. In this paper, we establish a two-stage vendor-buyer inventory system decision model by using bi-level decision making approach. The experimental result shows that the proposed bi-level decision model can effectively handle two-stage vendor-buyer inventory problems and obtain better results than the existing methods. © 2009 Springer-Verlag Berlin Heidelberg.

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http://hdl.handle.net/10453/10893