Risk Neutral Reformulation Approach to Risk Averse Stochastic Programming
Optimization and Control
2020-06-26 v4
Abstract
The aim of this paper is to show that in some cases risk averse multistage stochastic programming problems can be reformulated in a form of risk neutral setting. This is achieved by a change of the reference probability measure making ``bad" (extreme) scenarios more frequent. As a numerical example we demonstrate advantages of such change-of-measure approach applied to the Brazilian Interconnected Power System operation planning problem.
Cite
@article{arxiv.1901.01302,
title = {Risk Neutral Reformulation Approach to Risk Averse Stochastic Programming},
author = {Rui Peng Liu and Alexander Shapiro},
journal= {arXiv preprint arXiv:1901.01302},
year = {2020}
}