3 citations · 3 across the 1 of their papers we have counts for
3 papers
math.OC2021★ 3 cited
Heteroscedasticity-aware residuals-based contextual stochastic optimization
Rohit Kannan, Güzin Bayraksan, James Luedtke
We explore generalizations of some integrated learning and optimization frameworks for data-driven contextual stochastic optimization that can adapt to heteroscedasticity. We ident…
math.OC2019
Stochastic DC Optimal Power Flow With Reserve Saturation
Rohit Kannan, James R. Luedtke, Line A. Roald
We propose an optimization framework for stochastic optimal power flow with uncertain loads and renewable generator capacity. Our model follows previous work in assuming that gener…
math.OC2018
A stochastic approximation method for approximating the efficient frontier of chance-constrained nonlinear programs
Rohit Kannan, James Luedtke
We propose a stochastic approximation method for approximating the efficient frontier of chance-constrained nonlinear programs. Our approach is based on a bi-objective viewpoint of…