Solution Quality and Jackknife Estimators in Large Scale Hydroelectric Scheduling

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In stochastic programs the assessment of the solution quality is vital, especially when the size of the problem is so large that cannot be solved to optimality. We model a hydroelectric scheduling problem as a large-scale multi-stage stochastic linear program. We solve this problem via a sampling-based decomposition algorithm. We use Jackknife estimators for bias reduction when estimating the optimal value of the stochastic program.