Asymptotic convexity in multistage stochastic mixed-integer programs
We consider multistage stochastic mixed-integer programs M-SMIPs, and show that these problems are asymptotically convex. That is, we show that the expected cost-to-go functions in the problem converge to convex functions as the variability of the random parameters in the model increases. To derive this result, we first propose a novel adapted Gomory relaxation for … Read more