Robust inverse optimization
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Date
2018-05-01
Authors
Ghobadi, Kimia
Lee, Taewoo
Mahmoudzadeh, Houra
Terekhov, Daria
Advisor
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier
Abstract
Given 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.
Description
The 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/
Keywords
Dietary recommendation, Inverse optimization, Robust optimization