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Robust Optimization and Simulation of Production/inventory System with Stochastic Demand

In this paper a multi-stage multi-item production/inventory system with limited production capacity in stochastic demand environment is considered. We proposed a robust optimization model to deal with the uncertain market demands that are denoted as a number of discrete scenarios with known probabilities. An effective genetic algorithm is designed. The result of a simulation example shows that robust optimization is possible. By choice of proper programming weight omega, we can meet the stochastic demand with little error and very little cost.