Integrating facility location and production planning decisions
dc.contributor.author | Romeijn, H. Edwin | en_US |
dc.contributor.author | Sharkey, Thomas C. | en_US |
dc.contributor.author | Shen, Zuo-Jun Max | en_US |
dc.contributor.author | Zhang, Jiawei | en_US |
dc.date.accessioned | 2010-02-02T15:31:04Z | |
dc.date.available | 2011-03-01T16:26:44Z | en_US |
dc.date.issued | 2010-03 | en_US |
dc.identifier.citation | Romeijn, H. Edwin; Sharkey, Thomas C.; Shen, Zuo-Jun Max; Zhang, Jiawei (2010). "Integrating facility location and production planning decisions." Networks 55(2): 78-89. <http://hdl.handle.net/2027.42/64912> | en_US |
dc.identifier.issn | 0028-3045 | en_US |
dc.identifier.issn | 1097-0037 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/64912 | |
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. NETWORKS, 2010 | en_US |
dc.format.extent | 163779 bytes | |
dc.format.extent | 3118 bytes | |
dc.format.mimetype | application/pdf | |
dc.format.mimetype | text/plain | |
dc.publisher | Wiley Subscription Services, Inc., A Wiley Company | en_US |
dc.subject.other | Engineering | en_US |
dc.subject.other | Electronic, Electrical & Telecommunications Engineering | en_US |
dc.title | Integrating facility location and production planning decisions | en_US |
dc.type | Article | en_US |
dc.rights.robots | IndexNoFollow | en_US |
dc.subject.hlbsecondlevel | Industrial and Operations Engineering | en_US |
dc.subject.hlbsecondlevel | Management | en_US |
dc.subject.hlbsecondlevel | Economics | en_US |
dc.subject.hlbtoplevel | Engineering | en_US |
dc.subject.hlbtoplevel | Business | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Department of Industrial and Operations Engineering, The University of Michigan, Ann Arbor, Michigan 48109-2117 | en_US |
dc.contributor.affiliationother | Department of Decision Sciences and Engineering Systems, Rensselaer Polytechnic Institute, Troy, New York 12180-3590 ; Department of Decision Sciences and Engineering Systems, Rensselaer Polytechnic Institute, Troy, New York 12180-3590 | en_US |
dc.contributor.affiliationother | Department of Industrial Engineering and Operations Research, University of California, 4129 Etcheverry Hall, Berkeley, California 94720-1777 | en_US |
dc.contributor.affiliationother | IOMS-Operations Management, Stern School of Business, New York University, New York, New York 10012 | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/64912/1/20315_ftp.pdf | |
dc.identifier.doi | 10.1002/net.20315 | en_US |
dc.identifier.source | Networks | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
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