An Exact Method for Constrained Maximization of the Conditional Value-at-Risk of a Class of Stochastic Submodular Functions
Optimization and Control
2020-04-17 v3
Abstract
We consider a class of risk-averse submodular maximization problems (RASM) where the objective is the conditional value-at-risk (CVaR) of a random nondecreasing submodular function at a given risk level. We propose valid inequalities and an exact general method for solving RASM under the assumption that we have an efficient oracle that computes the CVaR of the random function. We demonstrate the proposed method on a stochastic set covering problem that admits an efficient CVaR oracle for the random coverage function.
Keywords
Cite
@article{arxiv.1903.08318,
title = {An Exact Method for Constrained Maximization of the Conditional Value-at-Risk of a Class of Stochastic Submodular Functions},
author = {Hao-Hsiang Wu and Simge Kucukyavuz},
journal= {arXiv preprint arXiv:1903.08318},
year = {2020}
}