On the estimation of Pareto fronts from the point of view of copula theory
A probabilistic framework is applied to Pareto front estimation. A link between Pareto front and level lines of a multivariate distribution is given. Parametric approximations of Pareto front are provided for Archimedean copulas. Consequences and limits of the Archimedean hypothesis are discussed. The full estimation methodology is analyzed on several examples.
pareto front copulas archimedean copulas multi-objective optimization