Technical note-a conic integer optimization approach to the constrained assortment problem under the mixed multinomial logit model

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dc.citation.epage1003en_US
dc.citation.issueNumber4en_US
dc.citation.spage994en_US
dc.citation.volumeNumber66en_US
dc.contributor.authorŞen, A.en_US
dc.contributor.authorAtamtürk, A.en_US
dc.contributor.authorKaminsky, P.en_US
dc.date.accessioned2019-02-21T16:07:31Z
dc.date.available2019-02-21T16:07:31Z
dc.date.issued2018en_US
dc.departmentDepartment of Industrial Engineeringen_US
dc.description.abstractWe consider the constrained assortment optimization problem under the mixed multinomial logit model. Even moderately sized instances of this problem are challenging to solve directly using standard mixed-integer linear optimization formulations. This has motivated recent research exploring customized optimization strategies and approximation techniques. In contrast, we develop a novel conic quadratic mixed-integer formulation. This new formulation, together with McCormick inequalities exploiting the capacity constraints, enables the solution of large instances using commercial optimization software.
dc.description.provenanceMade available in DSpace on 2019-02-21T16:07:31Z (GMT). No. of bitstreams: 1 Bilkent-research-paper.pdf: 222869 bytes, checksum: 842af2b9bd649e7f548593affdbafbb3 (MD5) Previous issue date: 2018en
dc.description.sponsorshipFunding:A. Şen was supported by a 2219 fellowship grant from the Scientific and Technological Research Council of Turkey (TÜBİTAK). He acknowledges with gratitude the financial support of TÜBİTAK and hospitality of the University of California, Berkeley. A. Atamtürk was supported, in part, by the Office of the Assistant Secretary of Defense for Research and Engineering [Grant FA9550-10-1-0168]. P. Kaminsky was supported, in part, by industry members of the I/UCRC Cen-ter for Excellence in Logistics and Distribution and by the National Science Foundation [Grant 1067994].
dc.identifier.doi10.1287/opre.2017.1703
dc.identifier.issn0030-364X
dc.identifier.urihttp://hdl.handle.net/11693/50368
dc.language.isoEnglish
dc.publisherINFORMS The Institute for Operations Research and the Management Sciences
dc.relation.isversionofhttps://doi.org/10.1287/opre.2017.1703
dc.relation.projectNational Science Foundation, NSF: 1067994 - University of California Berkeley, UC Berkeley - Office of the Assistant Secretary for Research and Technology, OST-R: FA9550-10-1-0168 - Türkiye Bilimsel ve Teknolojik Araştirma Kurumu, TÜBITAK
dc.source.titleOperations Researchen_US
dc.subjectAssortment optimizationen_US
dc.subjectConic integer optimizationen_US
dc.subjectMixed multinomial logiten_US
dc.titleTechnical note-a conic integer optimization approach to the constrained assortment problem under the mixed multinomial logit modelen_US
dc.typeArticleen_US

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