Abstract
We consider mixed integer programming (MIP) problems with uncertain data. Robust solutions to such problems are formulated as solutions of second-order cone programming problems with integer constraints, which can be solved by an adaptation of the Benders decomposition technique towards MIP with conic constraints. Preliminary numerical computation against robust 0-1 knapsack problems indicates that robustness can be achieved without substantial deterioration in optimal values.
