A Conic Integer Programming Approach to Constrained Assortment Optimization under the Mixed Multinomial Logit Model

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buir.contributor.authorŞen, Alper
buir.contributor.authorAtamtürk, Alper
dc.citation.epage1003en_US
dc.citation.issueNumber4en_US
dc.citation.spage994en_US
dc.citation.volumeNumber66en_US
dc.contributor.authorŞen, Alperen_US
dc.contributor.authorAtamtürk, Alperen_US
dc.contributor.authorKaminsky, P.en_US
dc.date.accessioned2019-01-29T14:43:56Z
dc.date.available2019-01-29T14:43:56Z
dc.date.issued2017-08-12en_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.en_US
dc.identifier.doi10.1287/ opre.2017.1703en_US
dc.identifier.eissn1526-5463
dc.identifier.issn0030-364X
dc.identifier.urihttp://hdl.handle.net/11693/48492
dc.language.isoEnglishen_US
dc.publisherInstitute for Operations Research and the Management Sciences (INFORMS)en_US
dc.relation.isversionofhttps://doi.org/10.1287/ opre.2017.1703en_US
dc.source.titleOperations Researchen_US
dc.subjectAssortment optimizationen_US
dc.subjectMixed multinomial logiten_US
dc.subjectConic integer programmingen_US
dc.titleA Conic Integer Programming Approach to Constrained Assortment Optimization under the Mixed Multinomial Logit Modelen_US
dc.typeArticleen_US

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