Work

On the Heavy-Tail Behavior of the Distributionally Robust Newsvendor

Year: 2021

Type: article

Abstract: Distributionally robust optimization is increasingly becoming a popular methodology to deal with uncertainty in optimization problems. Although the methodology optimizes for the worst-case distribution, a better understanding of the prescriptions from the models important from a practical perspective. In the paper “On the heavy-tail behavior of the distributionally robust newsvendor,” B. Das, A. Dhara, and K. Natarajan provide a novel analysis for the problem in the newsvendor setting with moment information. They show that the distributionally robust newsvendor by planning for the worst possible demand distribution with moment information will remains optimal if the true demand distribution is heavy-tailed. The prescribed optimal solution has a heavy-tail optimality’ property for free.

Source: Operations Research

DOI: 10.1287/opre.2020.2091

Authors: Bikramjit Das, Anulekha Dhara, Karthik Natarajan

Institution: Singapore University of Technology and Design

Language: English

Topic: Supply Chain and Inventory Management

Subfield: Management Information Systems

Field: Business, Management and Accounting

Domain: Social Sciences

Open Access status: green

Funders: Ministry of Education, India, Hong Kong University of Science and Technology, Singapore University of Technology and Design, International Design Centre

Award: G8375893933