this paper proposes a family of robust counterpart for uncertain linear programs (lp) which is obtained for a general definition of the uncertainty region. the relationship between uncertainty sets using norm bod-ies and their corresponding robust counterparts defined by dual norms is presented. those properties lead us to characterize primal and dual robust counterparts. the researchers show t...

Robust optimisation is a well established concept to deal with uncertainty. In particular, recovery-robust models are suitable for real-world contexts, where a certain amount of recovery – although limited – is often available. In this paper we describe a general framework to optimise event-based problems against delay propagation. We also present a real-world application to train platforming i...

In this paper we survey the primary research, both theoretical and applied, in the field of Robust Optimization (RO). Our focus will be on the computational attractiveness of RO approaches, as well as the modeling power and broad applicability of the methodology. In addition to surveying the most prominent theoretical results of RO over the past decade, we will also present some recent results ...