METHOD FOR OPTIMIZING RESERVOIR OPERATION FOR MULTIPLE OBJECTIVES BASED ON GRAPH CONVOLUTIONAL NEURAL NETWORK AND NSGA-II ALGORITHM

A method for optimizing a reservoir operation for multiple objectives based on a GCN and a NSGA-II algorithm. The method includes collecting relevant data for reservoir flood-control operation and establishing a multi-objective optimization model for the flood control. An initial population is obtained. Grouping individuals by an encoding operation and the grouped classifications are nodes of the GCN, and mapping parent-child relationships obtained by crossover and mutation operations as edges between the nodes in the GCN. A preliminary Pareto frontier is obtained, abscissas of the preliminary Pareto frontier are grouped and labeled, and a GCN model is trained by using the grouping labels and the graphic structure obtained in Step 2. The nodes in the graphic structure are classified by using the trained GCN model, and a uniformity of the Pareto frontier is adjusted. A set of non-inferior schemes of the multi-objective optimization problem for the reservoir operation is output.