Two Stage Stochastic Optimization

Minimizing costs in reservoir storage systems has been a challenging problem over the years. Several methods have been used previously to solve this problem. This paper would be considering the Two-Stage Stochastic Programming technique in solving this problem but the objective function would be a quadratic function. This function is the squared difference between release and the demand. Risk is also considered in solving this problem and the results are benchmarked against that of the Fletcher-Ponnambalam method. The results are also compared to that of the deterministic solution and the case of perfect information. The Two-Stage Stochastic Programming applied to a quadratic objective function gave promising results. As the number of scenarios increased, the optimal value approached that of the FP method. The stochastic solution from the TSP was shown to give 16.8% improvement in costs compared to the deterministic solution and the results of EVPI showed that getting perfect information for our problem would be highly beneficial leading to an 86.7% reduction in cost over time.