João Carlos Souza This paper studies the constrained multiobjective optimization problem of finding Pareto critical points of vector-valued functions. The proximal point method considered by Bonnel et al. (SIAM J. Optim., 4 (2005), pp. 953-970) is extended to locally Lipschitz functions in the finite dimensional multiobjective setting. To this end, a new approach for convergence analysis of the … Read more
A proximal linearized algorithm with a quasi distance as regularization term for minimizing a DC function (difference of two convex functions) is proposed. If the sequence generated by our algorithm is bounded, it is proved that every cluster point is a critical point of the function under consideration, even if minimizations are performed inexactly at … Read more
An extension of a proximal point algorithm for difference of two convex functions is presented in the context of Riemannian manifolds of nonposite sectional curvature. If the sequence generated by our algorithm is bounded it is proved that every cluster point is a critical point of the function (not necessarily convex) under consideration, even if … Read more