5 papers
Mitigating optimistic bias in entropic risk estimation and optimization
Utsav Sadana, Erick Delage, Angelos Georghiou
The entropic risk measure is widely used in high-stakes decision-making across economics, management science, finance, and safety-critical control systems because it captures tail…
Distributionally Robust Optimization with Decision-Dependent Information Discovery
Qing Jin, Angelos Georghiou, Phebe Vayanos +1
We study two-stage distributionally robust optimization (DRO) problems with decision-dependent information discovery (DDID) wherein (a portion of) the uncertain parameters are reve…
Inverse Optimization via Learning Feasible Regions
Ke Ren, Peyman Mohajerin Esfahani, Angelos Georghiou
We study inverse optimization (IO), where the goal is to use a parametric optimization program as the hypothesis class to infer relationships between input-decision pairs. Most of…
Robust Data-driven Prescriptiveness Optimization
Mehran Poursoltani, Erick Delage, Angelos Georghiou
The abundance of data has led to the emergence of a variety of optimization techniques that attempt to leverage available side information to provide more anticipative decisions. T…
A Robust Optimization Approach to Network Control Using Local Information Exchange
Georgios Darivianakis, Angelos Georghiou, Soroosh Shafiee +1
Designing policies for a network of agents is typically done by formulating an optimization problem where each agent has access to state measurements of all the other agents in the…