out-of-sample performance – Optimization Online

Robust Chance-Constrained Optimization using a Continuous Parameter Space Wasserstein-2 Ambiguity Set of Gaussian Mixtures

Published: 2026/07/18

Shibshankar Dey

Nonlinear Optimization, Robust Optimization, Stochastic Programming chance constraint, Gaussian mixture model (GMM), optimal transport, out-of-sample performance, wasserstein distance

We study distributionally robust linear chance-constrained problems in which uncertainty is modeled by a Gaussian mixture model (GMM). Finite-support distributionally robust (FDR) formulations, widely used in data-driven robust optimization, robustify over empirical mixture support points and therefore primarily stress-test the fitted nominal mixture. This can be insufficient when service reliability depends on structural misspecification of … Read more

Improving sample average approximation using distributional robustness

Published: 2019/10/03, Updated: 2019/10/04

Stochastic Programming distributional robustness, out-of-sample performance, sample average approximation

We consider stochastic optimization problems in which we aim to minimize the expected value of an objective function with respect to an unknown distribution of random parameters. We analyse the out-of-sample performance of solutions obtained by solving a distributionally robust version of the sample average approximation problem for unconstrained quadratic problems, and derive conditions under … Read more