Combining Machine Learning and Mathematical Optimization techniques to tackle IBM ILOG CPLEX automatic configuration on Hydro Unit Commitment problems

This work want to build an approach that can select the best algorithmic parameters of the optimization solver IBM ILOG CPLEX, for solving instances of a specific Hydro Unit Commitment problem, This goal is achieved by mixing Machine Learning and Mathematical optimization methods and algorithms