Distributionally robust joint chance constrained problem under moment uncertainty

4Citations
Citations of this article
10Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

We discuss and develop the convex approximation for robust joint chance constraints under uncertainty of first- and second-order moments. Robust chance constraints are approximated by Worst-Case CVaR constraints which can be reformulated by a semidefinite programming. Then the chance constrained problem can be presented as semidefinite programming. We also find that the approximation for robust joint chance constraints has an equivalent individual quadratic approximation form. © 2014 Ke-wei Ding.

Cite

CITATION STYLE

APA

Ding, K. W. (2014). Distributionally robust joint chance constrained problem under moment uncertainty. Journal of Applied Mathematics, 2014. https://doi.org/10.1155/2014/487178

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free