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A two-stage stochastic and robust programming approach to strategic planning of a reverse supply network: The case of paper recycling

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dc.contributor.authorKara, Selin Soner
dc.contributor.authorOnut, Semih
dc.contributor.institutionauthorÖNÜT, Semih
dc.date.accessioned2026-06-27T12:52:03Z
dc.date.issued2010
dc.description.abstractPaper is an example of a valuable material that can be recycled and recovered. In this study, a two-stage stochastic revenue-maximization model is presented to determine a long-term strategy under uncertainty for a large-scale real-world paper recycling company. This network-design problem includes optimal recycling center locations and optimal flow amounts between the nodes in the multi-facility environment. The proposed model is formulated with two-stage stochastic mixed-integer and robust programming approaches. The models are solved by commercial software GAMS 21.6/CPLEX 9.0 and the results are compared. The study is followed by the analyses of the results. (C) 2010 Elsevier Ltd. All rights reserved.en
dc.description.urihttps://doi.org/10.1016/j.eswa.2010.02.116
dc.identifier.doi10.1016/j.eswa.2010.02.116
dc.identifier.eissn1873-6793
dc.identifier.endpage6137
dc.identifier.issn0957-4174
dc.identifier.issue9
dc.identifier.startpage6129
dc.identifier.urihttps://hdl.handle.net/20.500.14981/47630
dc.identifier.volume37
dc.identifier.wos000278424600001
dc.language.isoeng
dc.publisherPERGAMON-ELSEVIER SCIENCE LTD
dc.relation.ispartofEXPERT SYSTEMS WITH APPLICATIONS
dc.subjectReverse supply network design
dc.subjectStochastic programming
dc.subjectRobust programming
dc.subjectPaper recycling
dc.subjectUncertainty
dc.subjectOPTIMIZATION MODEL
dc.subjectLOGISTICS
dc.subjectDESIGN
dc.subjectPRODUCT
dc.subjectSYSTEM
dc.subjectComputer Science
dc.subjectEngineering
dc.subjectOperations Research & Management Science
dc.titleA two-stage stochastic and robust programming approach to strategic planning of a reverse supply network: The case of paper recycling
dc.typeArticle
dspace.entity.typePublication
local.import.sourceWOS

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