Dam impoundment causes significant phosphorus (P) retention in reservoirs, leading to the emergence of legacy P release as a water quality threat under external pollution load reduction measures. Reservoir operations impact sediment P release through their complex influence on hydrodynamic and biogeochemical processes, but applicatory reservoir operation strategies for legacy P management have rarely been proposed. This study introduces a reservoir operation optimization approach for balancing economic objectives (i.e., water supply and hydropower generation) and P release mitigation. A coupled hydrodynamic-eutrophication-sediment model based on the Environmental Fluid Dynamics Code platform is used to simulate sediment P release under multiple reservoir operation scenarios. The resultant simulation data are used to train a dynamic artificial neural network (ANN) to model the response of P release to reservoir operations. By coupling the ANN with a reservoir operation model, we develop a multi-objective optimization model to refine reservoir operations for a three-tier tradeoff (i.e., water supply, hydropower generation and P release mitigation). China's Danjiangkou Reservoir is chosen as a case study to generate optimal operation rules. The optimal operation scheme decreases multi-year averaged annual P release by 19% (from 6688 tons to 5436 tons) while inversely increasing annual economic loss caused by water supply shortages by 14% and decreasing hydropower generation by 5%. Pareto-optimal solutions are subsequently generated to analyze tradeoffs between water supply/hydropower generation and P release mitigation. This study demonstrates the efficiency of using reservoir operations for legacy P management and offers an optimization tool for reservoir operation decision-making processes.