Integrated aggregate supply chain planning using memetic algorithm - A performance analysis case study

Fahimnia, B; Zanjirani Farahani, R; Sarkis, J

Integrated aggregate supply chain planning using memetic algorithm - A performance analysis case study

Fahimnia, B Zanjirani Farahani, R Sarkis, J

Permalink

Publisher:: Taylor & Francis Ltd
Publication Type:: Journal Article
Citation:: International Journal Of Production Research, 2013, 51 (18), pp. 5354 - 5373
Issue Date:: 2013-01

Closed Access

	Filename	Description	Size
	2012007636OK.pdf		1.76 MB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Fahimnia, B	en_US
dc.contributor.author	Zanjirani Farahani, R	en_US
dc.contributor.author	Sarkis, J	en_US
dc.date.issued	2013-01	en_US
dc.identifier.citation	International Journal Of Production Research, 2013, 51 (18), pp. 5354 - 5373	en_US
dc.identifier.issn	0020-7543	en_US
dc.identifier.uri	http://hdl.handle.net/10453/26969
dc.description.abstract	This paper aims to examine how a complex supply chain yields cost reduction benefits through the global integration of production and distribution decisions. The research is motivated by a complex real world supply chain planning problem facing a large automotive company. A mixed-integer nonlinear production-distribution planning model is solved using a customised memetic algorithm. The performance and effectiveness of the developed model and solution approach in achieving the global optimisation is investigated through experiments comparing the numerical results from the proposed integrated approach with those of a typical non-integrated (hierarchical) productiondistribution optimisation.	en_US
dc.publisher	Taylor & Francis Ltd	en_US
dc.relation.ispartof	International Journal Of Production Research	en_US
dc.relation.isbasedon	10.1080/00207543.2013.774492	en_US
dc.subject.classification	Operations Research	en_US
dc.title	Integrated aggregate supply chain planning using memetic algorithm - A performance analysis case study	en_US
dc.type	Journal Article
utslib.citation.volume	18	en_US
utslib.citation.volume	51	en_US
utslib.for	1503 Business and Management	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 Business
utslib.copyright.status	closed_access
pubs.consider-herdc	true	en_US
pubs.issue	18	en_US
pubs.volume	51	en_US

Abstract:

This paper aims to examine how a complex supply chain yields cost reduction benefits through the global integration of production and distribution decisions. The research is motivated by a complex real world supply chain planning problem facing a large automotive company. A mixed-integer nonlinear production-distribution planning model is solved using a customised memetic algorithm. The performance and effectiveness of the developed model and solution approach in achieving the global optimisation is investigated through experiments comparing the numerical results from the proposed integrated approach with those of a typical non-integrated (hierarchical) productiondistribution optimisation.

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

http://hdl.handle.net/10453/26969