4 papers · 1 filter
Don't Look Back in Anger: Wasserstein Distributionally Robust Optimization with Nonstationary Data
Dominic S. T. Keehan, Edward J. Anderson, Wolfram Wiesemann
We study data-driven decision problems where historical observations are generated by a time-evolving distribution whose consecutive shifts are bounded in Wasserstein distance. We…
Nonstationary Distribution Estimation via Wasserstein Probability Flows
Edward J. Anderson, Dominic S. T. Keehan
We study the problem of estimating a sequence of evolving probability distributions from historical data, where the underlying distribution changes over time in a nonstationary and…
On the Out-of-Sample Performance of Stochastic Dynamic Programming and Model Predictive Control
Dominic S. T. Keehan, Andrew B. Philpott, Edward J. Anderson
Sample average approximation--based stochastic dynamic programming (SDP) and model predictive control (MPC) are two different methods for approaching multistage stochastic optimiza…
Epi-Consistent Approximation of Stochastic Dynamic Programs
Dominic S. T. Keehan, Johannes O. Royset
We study the consistency of stochastic dynamic programs under converging probability distributions and other approximations. Utilizing results on the epi-convergence of expectation…