Two-sided linear chance constraints and extensions
Optimization and Control
2016-03-01 v2
Abstract
We examine the convexity and tractability of the two-sided linear chance constraint model under Gaussian uncertainty. We show that these constraints can be applied directly to model a larger class of nonlinear chance constraints as well as provide a reasonable approximation for a challenging class of quadratic chance constraints of direct interest for applications in power systems. With a view towards practical computations, we develop a second-order cone outer approximation of the two-sided chance constraint with provably small approximation error.
Cite
@article{arxiv.1507.01995,
title = {Two-sided linear chance constraints and extensions},
author = {Miles Lubin and Daniel Bienstock and Juan Pablo Vielma},
journal= {arXiv preprint arXiv:1507.01995},
year = {2016}
}