3 citations · 4 across the 4 of their papers we have counts for
4 papers
Decomposition and Adaptive Sampling for Data-Driven Inverse Linear Optimization
Rishabh Gupta, Qi Zhang
This work addresses inverse linear optimization where the goal is to infer the unknown cost vector of a linear program. Specifically, we consider the data-driven setting in which t…
A Unified Framework for Adjustable Robust Optimization with Endogenous Uncertainty
Qi Zhang, Wei Feng
This work proposes a framework for multistage adjustable robust optimization that unifies the treatment of three different types of endogenous uncertainty, where decisions, respect…
Multistage Robust Mixed-Integer Optimization Under Endogenous Uncertainty
Wei Feng, Yiping Feng, Qi Zhang
Endogenous, i.e. decision-dependent, uncertainty has received increased interest in the stochastic programming community. In the robust optimization context, however, it has rarely…
Branch-and-Price for a Class of Nonconvex Mixed-Integer Nonlinear Programs
Andrew Allman, Qi Zhang
This work attempts to combine the strengths of two major technologies that have matured over the last three decades: global mixed-integer nonlinear optimization and branch-and-pric…