Decomposition for adjustable robust linear optimization subject to uncertainty polytope
We present in this paper a general decomposition framework to solve exactly adjustable robust linear optimization problems subject to poly- tope uncertainty. Our approach is based on replacing the polytope by the set of its extreme points and generating the extreme points on the fly within row gen- eration or column-and-row generation algorithms. The novelty … Read more