Show simple item record

Exact algorithms for integrated facility location and production planning problems

dc.contributor.authorSharkey, Thomas C.en_US
dc.contributor.authorGeunes, Josephen_US
dc.contributor.authorEdwin Romeijn, H.en_US
dc.contributor.authorShen, Zuo‐jun Maxen_US
dc.date.accessioned2011-11-10T15:32:04Z
dc.date.available2012-10-01T18:34:20Zen_US
dc.date.issued2011-08en_US
dc.identifier.citationSharkey, Thomas C.; Geunes, Joseph; Edwin Romeijn, H.; Shen, Zuo‐jun Max (2011). "Exact algorithms for integrated facility location and production planning problems." Naval Research Logistics (NRL) 58(5): 419-436. <http://hdl.handle.net/2027.42/86850>en_US
dc.identifier.issn0894-069Xen_US
dc.identifier.issn1520-6750en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/86850
dc.description.abstractWe consider a class of facility location problems with a time dimension, which requires assigning every customer to a supply facility in each of a finite number of periods. Each facility must meet all assigned customer demand in every period at a minimum cost via its production and inventory decisions. We provide exact branch‐and‐price algorithms for this class of problems and several important variants. The corresponding pricing problem takes the form of an interesting class of production planning and order selection problems. This problem class requires selecting a set of orders that maximizes profit, defined as the revenue from selected orders minus production‐planning‐related costs incurred in fulfilling the selected orders. We provide polynomial‐time dynamic programming algorithms for this class of pricing problems, as well as for generalizations thereof. Computational testing indicates the advantage of our branch‐and‐price algorithm over various approaches that use commercial software packages. These tests also highlight the significant cost savings possible from integrating location with production and inventory decisions and demonstrate that the problem is rather insensitive to forecast errors associated with the demand streams. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011en_US
dc.publisherWiley Subscription Services, Inc., A Wiley Companyen_US
dc.subject.otherFacility Locationen_US
dc.subject.otherProduction Planningen_US
dc.subject.otherBranch and Priceen_US
dc.subject.otherOrder Selectionen_US
dc.titleExact algorithms for integrated facility location and production planning problemsen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelStatistics (Mathematical)en_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Industrial and Operations Engineering, The University of Michigan, Ann Arbor, Michigan 48109‐2117en_US
dc.contributor.affiliationotherDepartment of Industrial and Systems Engineering, Rensselaer Polytechnic Institute, Troy, New York 12180en_US
dc.contributor.affiliationotherDepartment of Industrial and Systems Engineering, University of Florida, Gainesville, Florida 32611‐6595en_US
dc.contributor.affiliationotherDepartment of Industrial Engineering and Operations Research, University of California, Berkeley, California 94720‐1777en_US
dc.contributor.affiliationotherDepartment of Industrial and Systems Engineering, Rensselaer Polytechnic Institute, Troy, New York 12180en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/86850/1/20458_ftp.pdf
dc.identifier.doi10.1002/nav.20458en_US
dc.identifier.sourceNaval Research Logistics (NRL)en_US
dc.identifier.citedreferenceA. Balakrishnan, J. Geunes, Requirements planning with substitutions: Exploiting bill‐of‐materials flexibility in production planning, Manuf Service Oper Manage 2 ( 2000 ), 166 – 185.en_US
dc.identifier.citedreferenceA. Balakrishnan, S. Graves, A composite algorithm for a concave‐cost network flow problem, Networks 19 ( 1989 ), 175 – 202.en_US
dc.identifier.citedreferenceC. Barnhart, E. L. Johnson, G. L. Nemhauser, M. W. P. Savelsbergh, P. H. Vance, Branch‐and‐price: Column generation for solving huge integer programs, Oper Res 46 ( 1998 ), 316 – 329.en_US
dc.identifier.citedreferenceP. Chardaire, A. Sutter, M. C. Costa, Solving the dynamic facility location problem, Networks 28 ( 1996 ), 117 – 124.en_US
dc.identifier.citedreferenceK. L. Croxton, B. Gendron, T. L. Magnanti, A comparison of mixed‐integer programming models for nonconvex piecewise linear cost minimization problems, Manage Sci 49 ( 2003 ), 1268 – 1273.en_US
dc.identifier.citedreferenceM. Daskin, C. Coullard, Z.‐J. Shen, An inventory‐location model: Formulation, solution algorithm, and computational results, Ann of Oper Res 10 ( 2001 ), 83 – 106.en_US
dc.identifier.citedreferenceM. S. Daskin, Network and discrete location: Models, algorithms, and applications, Wiley, New York, 1995.en_US
dc.identifier.citedreferenceE. V. Denardo, Dynamic programming: Models and applications, Prentice‐Hall, Englewood Cliffs, New Jersey, 1982.en_US
dc.identifier.citedreferenceR. Freling, H. E. Romeijn, D. Romero Morales, A. P. M. Wagelmans, A branch‐and‐price algorithm for the multi‐period single‐sourcing problem, Oper Res 51 ( 2003 ), 922 – 939.en_US
dc.identifier.citedreferenceJ. Geunes, H. E. Romeijn, K. Taaffe, Requirements planning with dynamic pricing and order selection flexibility, Oper Res 54 ( 2006 ), 394 – 401.en_US
dc.identifier.citedreferenceP. C. Gilmore, R. E. Gomory, A linear programming approach to the cutting‐stock problem, Oper Res 9 ( 1961 ), 849 – 859.en_US
dc.identifier.citedreferenceW. Huang, H. E. Romeijn, J. Geunes, The continuous‐time single‐sourcing problem with capacity expansion opportunities, Naval Res Logist 52 ( 2005 ), 193 – 211.en_US
dc.identifier.citedreferenceJ. Krarup, O. Bilde, Plant location, set covering, and economic lot size: An O ( m n ) ‐algorithm for structured problems, L. Collatz, W. Wetterling (Editors), Numerische Methoden Bei Optimierungsaufgaben, Band 3: Optimierung Bei Graph‐Theoretischen Und Ganzahligen Problemen, Birkhauser, Basel, 1977, pp. 155 – 180.en_US
dc.identifier.citedreferenceS. F. Love, Bounded production and inventory models with piecewise concave costs, Manage Sci 20 ( 1973 ), 313 – 318.en_US
dc.identifier.citedreferenceT. Magnanti, Z.‐J. Shen, J. Shu, D. Simchi‐Levi, C.‐P. Teo, Inventory placement in acyclic supply chain networks, Oper Res Lett 34 ( 2006 ), 228 – 238.en_US
dc.identifier.citedreferenceH. E. Romeijn, D. Romero Morales, A probabilistic analysis of the multi‐period single‐sourcing problem, Discrete Appl Math 112 ( 2001 ), 301 – 328.en_US
dc.identifier.citedreferenceH. E. Romeijn, D. Romero Morales, An asymptotically optimal greedy heuristic for the multi‐period single‐sourcing problem: The cyclic case, Naval Res Logist 50 ( 2003 ), 412 – 437.en_US
dc.identifier.citedreferenceH. E. Romeijn, D. Romero Morales, Asymptotic analysis of a greedy heuristic for the multi‐period single‐sourcing problem: The acyclic case, J Heurist 10 ( 2004 ), 5 – 35.en_US
dc.identifier.citedreferenceH. E. Romeijn, T. C. Sharkey, Z. J. Shen, J. Zhang, Integrating facility location and production planning decisions, Networks 55 ( 2010 ), 78 – 89.en_US
dc.identifier.citedreferenceT. J. Van Roy, D. Erlenkotter, A dual‐based procedure for dynamic facility location, Manage Sci 28 ( 1982 ), 1091 – 1105.en_US
dc.identifier.citedreferenceM. P. W. Savelsbergh, A branch–and–price algorithm for the generalized assignment problem, Oper Res 45 ( 1997 ), 831 – 841.en_US
dc.identifier.citedreferenceJ. F. Shapiro, Modeling the supply chain, Duxbury, Pacific Grove, CA, 2001.en_US
dc.identifier.citedreferenceZ. J. Shen, C. Coullard, M. S. Daskin, A joint location‐inventory model, Transport Sci 37 ( 2003 ), 40 – 55.en_US
dc.identifier.citedreferenceJ. Shu, C. P. Teo, Z. J. Shen, Stochastic transportation‐inventory network design problem, Oper Res 53 ( 2005 ), 48 – 60.en_US
dc.identifier.citedreferenceA. F. Veinott, Minimum concave cost solutions of Leontief substitution models of multi‐facility inventory systems, Oper Res 17 ( 1969 ), 262 – 291.en_US
dc.identifier.citedreferenceH. M. Wagner, A postscript to dynamic problems of the theory of the firm, Naval Res Logist Quart 7 ( 1960 ), 7 – 12.en_US
dc.identifier.citedreferenceH. M. Wagner, T. M. Whitin, Dynamic version of the economic lot size model, Manage Sci 5 ( 1958 ), 89 – 96.en_US
dc.identifier.citedreferenceG. O. Wesolowsky, Dynamic facility location, Manage Sci 19 ( 1973 ), 1241 – 1248.en_US
dc.identifier.citedreferenceS. D. Wu, H. Golbasi, Multi‐item, multi‐facility supply chain planning: Models, complexities, and algorithms, Comput Optim Appl 28 ( 2004 ), 325 – 356.en_US
dc.identifier.citedreferenceP. H. Zipkin, Foundations of inventory management ( 2000 ).en_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


Files in this item

Show simple item record

Remediation of Harmful Language

The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.

Accessibility

If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.