Sampling methods for multistage robust convex optimization problems
Optimization and Control
2016-11-08 v2
Abstract
In this paper, probabilistic guarantees for constraint sampling of multistage robust convex optimization problems are derived. The dynamic nature of these problems is tackled via the so-called scenario-with-certificates approach. This allows to avoid the conservative use of explicit parametrizations through decision rules, and provides a significant reduction of the sample complexity to satisfy a given level of reliability. An explicit bound on the probability of violation is also given. Numerical results dealing with a multistage inventory management problem show the efficacy of the proposed approach.
Keywords
Cite
@article{arxiv.1611.00980,
title = {Sampling methods for multistage robust convex optimization problems},
author = {Francesca Maggioni and Marida Bertocchi and Fabrizio Dabbene and Roberto Tempo},
journal= {arXiv preprint arXiv:1611.00980},
year = {2016}
}