Regret Minimization for Robust and Satisficing Monopolists
Abstract:
In this talk, we present a series of work concerning a seller who aspires to sell an item(s) to a buyer(s) with limited information. When there is only one item and one buyer, a mechanism that minimizes the worst-case regret of the seller has been previously derived in the literature. In the first part of the talk, we use robust optimization and linear program duality to extend this result to the setting of multiple items and multiple buyers. In the second half of the talk, we show how to alleviate the conservatism of robust optimization using a relatively new concept of robust satisficing which aims at minimizing the excess regret over the predetermined threshold. For every mechanism design problem presented in this talk, we show that it admits an analytical solution and can therefore be readily adopted by interested practitioners.
About Napat Rujeerapaiboon:
Napat Rujeerapaiboon holds an assistant professorship at the Department of Industrial Systems Engineering and Management at the National University of Singapore. His research primarily focuses on developing new frameworks for optimization under uncertainty, particularly robust and distributionally robust optimization, and their applications in finance, economics, and energy. He has published his work in the majority of prestigious journals in operations research, management science and mathematical optimization. Besides, he has received numerous teaching awards from the university and several fundings to advance his research projects from the Ministry of Education, Singapore.
Language: English
This is a free seminar. Registration is mandatory
Supported by the Fond National de la Recherche,
Luxembourg (17931929)