This paper presents an automatic multiobjective hydrodynamic optimization strategy for pump–turbine impellers. In the strategy, the blade shape is parameterized based on the blade loading distribution using an inverse design method. An efficient response surface model relating the design parameters and the objective functions is obtained. Then, a multiobjective evolutionary algorithm is applied to the response surface functions to find a Pareto front for the final trade-off selection. The optimization strategy was used to redesign a scaled pump–turbine. Model tests were conducted to validate the final design and confirm the validity of the design strategy.