BIRS Workshop Lecture Videos
On the Heavy-Tail Behavior of the Distributionally Robust Newsvendor Model with Moment Constraints Natarajan, Karthik
Since the seminal work of Scarf (1958) on the newsvendor problem with ambiguity in the demand distribution, there has been a growing interest in the study of the distributionally robust newsvendor problem. Scarf's solution is criticized at times for being overly conservative since the worst-case distribution is discrete with a few support points. A simple observation however indicates that the optimal order quantity in this two moment model is also optimal for a censored student-t distribution with infinite variance for all possible values of the critical ratio. In this paper, we generalize this ``heavy tail optimality" property of the distributionally robust newsvendor to the case when information on the first and the nth moment is known for any rational number n > 1. This is joint work with Anulekha Dhara (University of Michigan) and Bikramjit Das (SUTD).
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