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Article: Integrating facility location and production planning decisions

TitleIntegrating facility location and production planning decisions
Authors
KeywordsComputational complexity
Approximation algorithms
Production planning
Facility location
Issue Date2010
Citation
Networks, 2010, v. 55, n. 2, p. 78-89 How to Cite?
AbstractWe consider a metric uncapacitated facility location problem where we must assign each customer to a facility and meet the demand of the customer in future time periods through production and inventory decisions at the facility. We show that the problem, in general, is as hard to approximate as the set cover problem. We therefore focus on developing approximation algorithms for special cases of the problem. These special cases come in two forms: (i) specialize the production and inventory cost structure and (ii) specialize the demand pattern of the customers. In the former, we offer reductions to variants of the metric uncapacitated facility location problem that have been previously studied. The latter gives rise to a class of metric uncapacitated facility location problems where the facility cost function is concave in the amount of demand assigned to the facility. We develop a modified greedy algorithm together with the idea of cost-scaling to provide an algorithm for this class of problems with an approximation guarantee of 1.52. © 2009 Wiley Periodicals, Inc.
Persistent Identifierhttp://hdl.handle.net/10722/296059
ISSN
2023 Impact Factor: 1.6
2023 SCImago Journal Rankings: 0.908
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorRomeijn, H. Edwin-
dc.contributor.authorSharkey, Thomas C.-
dc.contributor.authorShen, Zuo Jun Max-
dc.contributor.authorZhang, Jiawei-
dc.date.accessioned2021-02-11T04:52:45Z-
dc.date.available2021-02-11T04:52:45Z-
dc.date.issued2010-
dc.identifier.citationNetworks, 2010, v. 55, n. 2, p. 78-89-
dc.identifier.issn0028-3045-
dc.identifier.urihttp://hdl.handle.net/10722/296059-
dc.description.abstractWe consider a metric uncapacitated facility location problem where we must assign each customer to a facility and meet the demand of the customer in future time periods through production and inventory decisions at the facility. We show that the problem, in general, is as hard to approximate as the set cover problem. We therefore focus on developing approximation algorithms for special cases of the problem. These special cases come in two forms: (i) specialize the production and inventory cost structure and (ii) specialize the demand pattern of the customers. In the former, we offer reductions to variants of the metric uncapacitated facility location problem that have been previously studied. The latter gives rise to a class of metric uncapacitated facility location problems where the facility cost function is concave in the amount of demand assigned to the facility. We develop a modified greedy algorithm together with the idea of cost-scaling to provide an algorithm for this class of problems with an approximation guarantee of 1.52. © 2009 Wiley Periodicals, Inc.-
dc.languageeng-
dc.relation.ispartofNetworks-
dc.subjectComputational complexity-
dc.subjectApproximation algorithms-
dc.subjectProduction planning-
dc.subjectFacility location-
dc.titleIntegrating facility location and production planning decisions-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1002/net.20315-
dc.identifier.scopuseid_2-s2.0-77049124817-
dc.identifier.volume55-
dc.identifier.issue2-
dc.identifier.spage78-
dc.identifier.epage89-
dc.identifier.eissn1097-0037-
dc.identifier.isiWOS:000274946600002-
dc.identifier.issnl0028-3045-

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