We propose a steepest descent method for unconstrained multicriteria optimization and a
“feasible descent direction” method for the constrained case. In the unconstrained case, the …

We propose an extension of Newton's method for unconstrained multiobjective optimization
(multicriteria optimization). This method does not use a priori chosen weighting factors or …

In this work we propose a Cauchy-like method for solving smooth unconstrained vector
optimization problems. When the partial order under consideration is the one induced by the …

In this paper, we deal with the class of unconstrained multi-objective optimization problems.
In this setting we introduce, for the first time in the literature, a Limited Memory Quasi-Newton …

We present a rigorous and comprehensive survey on extensions to the multicriteria setting of
three well-known scalar optimization algorithms. Multiobjective versions of the steepest …

In this work, we propose an inexact projected gradient-like method for solving smooth
constrained vector optimization problems. In the unconstrained case, we retrieve the …

In 2004, Graña Drummond and Iusem proposed an extension of the projected gradient
method for constrained vector optimization problems. Using this method, an Armijo-like rule …

We consider the projected gradient method for solving the problem of finding a Pareto
optimum of a quasiconvex multiobjective function. We show convergence of the sequence …

In this paper, we propose an adaptation of the classical augmented Lagrangian method for
dealing with multi-objective optimization problems. Specifically, after a brief review of the …

We propose and analyse a nonmonotone quasi-Newton algorithm for unconstrained
strongly convex multiobjective optimization. In our method, we allow for the decrease of a …