File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Stochastic transportation-inventory network design problem

TitleStochastic transportation-inventory network design problem
Authors
KeywordsInventory/production: uncertainty, stochastic
Facilities/equipment planning: stochastic
Programming: nonlinear
Issue Date2005
Citation
Operations Research, 2005, v. 53, n. 1, p. 48-60 How to Cite?
AbstractWe study the stochastic transportation-inventory network design problem involving one supplier and multiple retailers. Each retailer faces some uncertain demand, and safety stock must be maintained to achieve suitable service levels. However, risk-pooling benefits may be achieved by allowing some retailers to serve as distribution centers for other retailers. The problem is to determine which retailers should serve as distribution centers and how to allocate the other retailers to the distribution centers. Shen et al. (2003) formulated this problem as a set-covering integer-programming model. The pricing problem that arises from the column generation algorithm gives rise to a new class of the submodular function minimization problem. In this paper, we show that by exploiting certain special structures, we can solve the general pricing problem in Shen et al. efficiently. Our approach utilizes the fact that the set of all lines in a two-dimension plane has low VC-dimension. We present computational results on several instances of sizes ranging from 40 to 500 retailers. Our solution technique can be applied to a wide range of other concave cost-minimization problems. © 2005 INFORMS.
Persistent Identifierhttp://hdl.handle.net/10722/296026
ISSN
2023 Impact Factor: 2.2
2023 SCImago Journal Rankings: 2.848
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorShu, Jia-
dc.contributor.authorTeo, Chung Piaw-
dc.contributor.authorShen, Zuo Jun Max-
dc.date.accessioned2021-02-11T04:52:40Z-
dc.date.available2021-02-11T04:52:40Z-
dc.date.issued2005-
dc.identifier.citationOperations Research, 2005, v. 53, n. 1, p. 48-60-
dc.identifier.issn0030-364X-
dc.identifier.urihttp://hdl.handle.net/10722/296026-
dc.description.abstractWe study the stochastic transportation-inventory network design problem involving one supplier and multiple retailers. Each retailer faces some uncertain demand, and safety stock must be maintained to achieve suitable service levels. However, risk-pooling benefits may be achieved by allowing some retailers to serve as distribution centers for other retailers. The problem is to determine which retailers should serve as distribution centers and how to allocate the other retailers to the distribution centers. Shen et al. (2003) formulated this problem as a set-covering integer-programming model. The pricing problem that arises from the column generation algorithm gives rise to a new class of the submodular function minimization problem. In this paper, we show that by exploiting certain special structures, we can solve the general pricing problem in Shen et al. efficiently. Our approach utilizes the fact that the set of all lines in a two-dimension plane has low VC-dimension. We present computational results on several instances of sizes ranging from 40 to 500 retailers. Our solution technique can be applied to a wide range of other concave cost-minimization problems. © 2005 INFORMS.-
dc.languageeng-
dc.relation.ispartofOperations Research-
dc.subjectInventory/production: uncertainty, stochastic-
dc.subjectFacilities/equipment planning: stochastic-
dc.subjectProgramming: nonlinear-
dc.titleStochastic transportation-inventory network design problem-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1287/opre.1040.0140-
dc.identifier.scopuseid_2-s2.0-14644433042-
dc.identifier.volume53-
dc.identifier.issue1-
dc.identifier.spage48-
dc.identifier.epage60-
dc.identifier.isiWOS:000228443300004-
dc.identifier.issnl0030-364X-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats