1. A computer-implemented method for multi-objective optimization of an aerodynamic or hydrodynamic design, comprising the steps of: (a) providing an initial population of solutions as a parent population; (b) partitioning said parent population into a number of clusters; (c) determining a convergence ratio (Ψ) for each of said clusters; (d) determining whether the convergence ratio (Ψ) of each cluster is larger than a given threshold value (ρ), (e1) generating offspring using a model when the convergence ratio (Ψ) is smaller or equal to the given threshold value (ρ), wherein the model uses an estimation of distribution algorithm (EDA) and the model includes a deterministic part and a stochastic part; (e2) generating offspring using mutation and crossover when the convergence ratio (Ψ) is larger than the given threshold value (ρ); (f) merging parents and offspring; (g) creating a new parent population using a Pareto-based selection method; and (h) repeating steps (b) through (g) using the new parent population, until a stop criterion is met.