Title
Preference Robust Optimization
Abstract
Preference robust optimization concerns decision making problems where the decision maker’s utility/risk preference is ambiguous and the optimal decision is based on the worst case utility function or risk measure from a set of plausible utility functions/risk measures constructed with partially available information. In this talk, we will discuss some PRO models based on the expected utility theory and the dual theory of choice, their computational schemes and underlying theory. In the case when the decision maker’s preference is inconsistent/state-dependent, we propose a distributionally preference robust model on the basis of random utility theory and extend the framework to spectral risk management problems.
Bio
Huifu Xu is a Professor of the Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong. Prior to joining CUHK in 2019, he was a professor of operational research in the School of Mathematical Sciences, University of Southampton. Huifu Xu’s research is mainly on optimal decision making under uncertainty including stochastic mathematical programs with equilibrium constraints (SMPEC), stochastic generalized equations and distributionally robust optimization with applications in energy markets. More recently, he is actively working on preference robust optimization and statistical robustness in data-driven problems.