This paper is concerned with the use of simulation in computing predictors in settings in which real-world observations are collected. A major challenge is that the state description underlying the…
This paper introduces a new asymptotic regime for simplifying stochastic models having nonstationary effects, such as those that arise in the presence of time-of-day effects. This regime describes …
We study statistical inference and distributionally robust solution methods for stochastic optimization problems, focusing on confidence intervals for optimal values and solutions that achieve exac…