Function approximation for a production and storage problem under uncertainty

In this work, we present an approximate value iteration algorithm for a production and storage model with multiple production stages and a single final product, subject to random demand. We use linear function approximation schemes in subsets of the state space and represent a few key states in a look-up table form. We obtain some promising results and perform sensitivity analysis with respect to the parameters of the algorithm for the benchmark problem studied.