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dc.contributor.authorGhobadi, Kimia
dc.contributor.authorLee, Taewoo
dc.contributor.authorMahmoudzadeh, Houra
dc.contributor.authorTerekhov, Daria
dc.date.accessioned2018-05-10 13:37:12 (GMT)
dc.date.available2018-05-10 13:37:12 (GMT)
dc.date.issued2018-05-01
dc.identifier.urihttp://dx.doi.org/10.1016/j.orl.2018.03.007
dc.identifier.urihttp://hdl.handle.net/10012/13278
dc.descriptionThe final publication is available at Elsevier via http://dx.doi.org/10.1016/j.orl.2018.03.007 © 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.description.abstractGiven an observation of a decision-maker’s uncertain behavior, we develop a robust inverse optimization model for imputing an objective function that is robust against mis-specifications of the behavior. We characterize the inversely optimized cost vectors for uncertainty sets that may or may not intersect the feasible region, and propose tractable solution methods for special cases. We demonstrate the proposed model in the context of diet recommendation.en
dc.language.isoenen
dc.publisherElsevieren
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectDietary recommendationen
dc.subjectInverse optimizationen
dc.subjectRobust optimizationen
dc.titleRobust inverse optimizationen
dc.typeArticleen
dcterms.bibliographicCitationGhobadi, K., Lee, T., Mahmoudzadeh, H., & Terekhov, D. (2018). Robust inverse optimization. Operations Research Letters, 46(3), 339–344. https://doi.org/10.1016/j.orl.2018.03.007en
uws.contributor.affiliation1Faculty of Engineeringen
uws.contributor.affiliation2Management Sciencesen
uws.typeOfResourceTexten
uws.typeOfResourceTexten
uws.peerReviewStatusRevieweden
uws.scholarLevelFacultyen


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