In this paper, we propose a projected subgradient method for solving constrained
nondifferentiable quasiconvex multiobjective optimization problems. The algorithm is based …

We propose new descent methods for unconstrained multiobjective optimization problems,
where each objective function can be written as the sum of a continuously differentiable …

A simple multi-objective cross-entropy method is presented in this paper, with only four
parameters that facilitate the initial setting and tuning of the proposed strategy. The effects of …

We prove that every strongly quasiconvex function is 2-supercoercive (in particular,
coercive). Furthermore, we investigate the usual properties of proximal operators for strongly …

In this paper, a globally convergent Newton-type proximal gradient method is developed for
composite multi-objective optimization problems where each objective function can be …

In this paper, we propose a new descent method, called multiobjective memory gradient
method, for finding Pareto critical points of a multiobjective optimization problem. The main …

In this paper, we present two inexact scalarization proximal point methods to solve
quasiconvex multiobjective minimization problems on Hadamard manifolds. Under standard …

We present an efficient descent method for unconstrained, locally Lipschitz multiobjective
optimization problems. The method is realized by combining a theoretical result regarding …

We consider a projected gradient method equipped with the nonmonotone line search
procedure for convex constrained multiobjective optimization problems. Under mild …

An algorithm for solving the expectation formulation of stochastic nonsmooth multiobjective
optimization problems is proposed. The proposed method is an extension of the classical …