Robust Linear Programming with Norm Uncertainty

Abstract

We consider the linear programming problem with uncertainty set described by $\left(p,w\right)$-norm. We suggest that the robust counterpart of this problem is equivalent to a computationally convex optimization problem. We provide probabilistic guarantees on the feasibility of an optimal robust solution when the uncertain coefficients obey independent and identically distributed normal distributions.