Polymatroids and mean-risk minimization in discrete optimization

We study discrete optimization problems with a submodular mean-risk minimization objective. For 0–1 problems a linear characterization of the convex lower envelope is given. For mixed 0–1 problems we derive an exponential class of conic quadratic valid inequalities. We report computational experiments on risk-averse capital budgeting problems with uncertain returns.