Open AccessProximal point algorithm for differentiable quasi-convex multiobjective optimization
Author(s) -
Fouzia Amir,
Ali Farajzadeh,
Narin Petrot
Publication year - 2020
Publication title -
filomat
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.449
H-Index - 34
eISSN - 2406-0933
pISSN - 0354-5180
DOI - 10.2298/fil2007367a
Subject(s) - mathematics , differentiable function , lipschitz continuity , mathematical optimization , convex function , proximal gradient methods , regular polygon , point (geometry) , pareto principle , convex optimization , optimization problem , function (biology) , multi objective optimization , mathematical analysis , geometry , evolutionary biology , biology
The main aim of this paper is to consider the proximal point method for solving multiobjective optimization problem under the differentiability, locally Lipschitz and quasi-convex conditions of the objective function. The control conditions to guarantee that the accumulation points of any generated sequence, are Pareto critical points are provided.