Cutting planes for multi-stage stochastic integer programs

This paper addresses the problem of finding cutting planes for multi-stage stochastic integer programs. We give a general method for generating cutting planes for multi-stage stochastic integer programs based on combining inequalities that are valid for the individual scenarios. We apply the method to generate cuts for a stochastic version of a dynamic knapsack problem and to stochastic lot sizing problems. We give computational results which show that these new inequalities are very effective in a branch-and-cut algorithm