Particle swarm optimization for bi-level pricing problems in supply chains

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

Particle swarm optimization for bi-level pricing problems in supply chains

Gao, Y Zhang, G

Lu, J

Wee, HM

Permalink

Publication Type:: Journal Article
Citation:: Journal of Global Optimization, 2011, 51 (2), pp. 245 - 254
Issue Date:: 2011-10-01

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

Adobe PDF

Download full textAdobe PDF (174.09 kB)

View on publisher's site

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	Gao, Y	en_US
dc.contributor.author	Zhang, G https://orcid.org/0000-0003-3960-0583	en_US
dc.contributor.author	Lu, J https://orcid.org/0000-0003-0690-4732	en_US
dc.contributor.author	Wee, HM	en_US
dc.date.issued	2011-10-01	en_US
dc.identifier.citation	Journal of Global Optimization, 2011, 51 (2), pp. 245 - 254	en_US
dc.identifier.issn	0925-5001	en_US
dc.identifier.uri	http://hdl.handle.net/10453/17944
dc.description.abstract	With rapid technological innovation and strong competition in hi-tech industries such as computer and communication organizations, the upstream component price and the downstream product cost usually decline significantly with time. As a result, an effective pricing supply chain model is very important. This paper first establishes two bi-level pricing models for pricing problems with the buyer and the vendor in a supply chain designated as the leader and the follower, respectively. A particle swarm optimization (PSO) based algorithm is developed to solve problems defined by these bi-level pricing models. Experiments illustrate that this PSO based algorithm can achieve a profit increase for buyers or vendors if they are treated as the leaders under some situations, compared with the existing methods. © 2010 Springer Science+Business Media, LLC.	en_US
dc.relation.ispartof	Journal of Global Optimization	en_US
dc.relation.isbasedon	10.1007/s10898-010-9595-8	en_US
dc.subject.classification	Operations Research	en_US
dc.title	Particle swarm optimization for bi-level pricing problems in supply chains	en_US
dc.type	Journal Article
utslib.citation.volume	2	en_US
utslib.citation.volume	51	en_US
utslib.for	0802 Computation Theory and Mathematics	en_US
utslib.for	0103 Numerical and Computational Mathematics	en_US
utslib.for	0102 Applied Mathematics	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	open_access
pubs.issue	2	en_US
pubs.publication-status	Published	en_US
pubs.volume	51	en_US

Abstract:

With rapid technological innovation and strong competition in hi-tech industries such as computer and communication organizations, the upstream component price and the downstream product cost usually decline significantly with time. As a result, an effective pricing supply chain model is very important. This paper first establishes two bi-level pricing models for pricing problems with the buyer and the vendor in a supply chain designated as the leader and the follower, respectively. A particle swarm optimization (PSO) based algorithm is developed to solve problems defined by these bi-level pricing models. Experiments illustrate that this PSO based algorithm can achieve a profit increase for buyers or vendors if they are treated as the leaders under some situations, compared with the existing methods. © 2010 Springer Science+Business Media, LLC.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/17944