Multi-Attribute Utility Preference Robust Optimization and Robust Spectral Risk Optimization

H. Xu

Decision maker’s preference in utility or risk determines which utility function or risk measure to use in an optimal decision making problem.

Ambiguity arises when there is incomplete information about decision maker’s preference and such ambiguity is ubiquitous in multi-attribute decision making problems such as healthcare management, network management, airport operations management, finance and supply chain management.

In this project, we will propose various preference robust optimization models which can be effectively used to mitigate the risks arising from the endogenous preference uncertainty, and develop efficient computational methods for solving the resulting robust optimization problems. We will also develop the underlying theory which can be effectively used to examine stability of the proposed models and numerical schemes in a data-driven environment.