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Article: Integrating facility location and production planning decisions
Title | Integrating facility location and production planning decisions |
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Authors | |
Keywords | Computational complexity Approximation algorithms Production planning Facility location |
Issue Date | 2010 |
Citation | Networks, 2010, v. 55, n. 2, p. 78-89 How to Cite? |
Abstract | We 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 Identifier | http://hdl.handle.net/10722/296059 |
ISSN | 2023 Impact Factor: 1.6 2023 SCImago Journal Rankings: 0.908 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Romeijn, H. Edwin | - |
dc.contributor.author | Sharkey, Thomas C. | - |
dc.contributor.author | Shen, Zuo Jun Max | - |
dc.contributor.author | Zhang, Jiawei | - |
dc.date.accessioned | 2021-02-11T04:52:45Z | - |
dc.date.available | 2021-02-11T04:52:45Z | - |
dc.date.issued | 2010 | - |
dc.identifier.citation | Networks, 2010, v. 55, n. 2, p. 78-89 | - |
dc.identifier.issn | 0028-3045 | - |
dc.identifier.uri | http://hdl.handle.net/10722/296059 | - |
dc.description.abstract | We 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.language | eng | - |
dc.relation.ispartof | Networks | - |
dc.subject | Computational complexity | - |
dc.subject | Approximation algorithms | - |
dc.subject | Production planning | - |
dc.subject | Facility location | - |
dc.title | Integrating facility location and production planning decisions | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1002/net.20315 | - |
dc.identifier.scopus | eid_2-s2.0-77049124817 | - |
dc.identifier.volume | 55 | - |
dc.identifier.issue | 2 | - |
dc.identifier.spage | 78 | - |
dc.identifier.epage | 89 | - |
dc.identifier.eissn | 1097-0037 | - |
dc.identifier.isi | WOS:000274946600002 | - |
dc.identifier.issnl | 0028-3045 | - |