Abstract: A joint multi-objective reservoir impoundment framework is proposed and optimized through district division strategy, aggregation-decomposition and parameter-simulation-optimization approaches, and parallel progressive optimization algorithm. The mega groups imposed of 30 reservoirs in the upper Yangtze River were selected as case study. Application results demonstrate that the proposed model and framework can solve the complex problem of optimal operation of joint impoundment of large reservoir groups. Intelligent algorithm can produce a large number of non-inferior solutions for multi-objective optimization problems with complex constraints. The distribution of Pareto frontiers is uniform and extensive, providing flexible scheduling for decision makers. Compared with the original impoundment operation rule, the optimal solution can enhance total impoundment efficiency from 90.40% to 94.42% and increase 7.65 billion kWh (3.76%) power generation annually under controllable flood risk.