Robust two-stage combinatorial optimization problems under convex uncertainty
Data Structures and Algorithms
2019-05-08 v1 Optimization and Control
Abstract
In this paper a class of robust two-stage combinatorial optimization problems is discussed. It is assumed that the uncertain second stage costs are specified in the form of a convex uncertainty set, in particular polyhedral or ellipsoidal ones. It is shown that the robust two-stage versions of basic network and selection problems are NP-hard, even in a very restrictive cases. Some exact and approximation algorithms for the general problem are constructed. Polynomial and approximation algorithms for the robust two-stage versions of basic problems, such as the selection and shortest path problems, are also provided.
Cite
@article{arxiv.1905.02469,
title = {Robust two-stage combinatorial optimization problems under convex uncertainty},
author = {Marc Goerigk and Adam Kasperski and Pawel Zielinski},
journal= {arXiv preprint arXiv:1905.02469},
year = {2019}
}