Regularization Proximal Method for Monotone Variational Inclusions

2021 ◽  
Author(s):  
Dang Van Hieu ◽  
Pham Ky Anh ◽  
Nguyen Hai Ha
Keyword(s):  
Variational Inclusions ◽  
Proximal Method

scholarly journals On a System of Nonlinear Variational Inclusions withHh,η-Monotone Operators

2012 ◽  
Vol 2012 ◽  
pp. 1-21 ◽  
Author(s):  
Zeqing Liu ◽  
Jeong Sheok Ume ◽  
Shin Min Kang
Keyword(s):  
Hilbert Spaces ◽  
Monotone Operators ◽  
Variational Inclusions ◽  
Iterative Approximation

This paper is concerned mainly with the existence and iterative approximation of solutions for a system of nonlinear variational inclusions involving the stronglyHh,η-monotone operators in Hilbert spaces. The results presented in this paper extend, improve, and unify many known results in the literature.

A new logarithmic-quadratic proximal method for nonlinear complementarity problems

2009 ◽  
Vol 215 (2) ◽  
pp. 695-706 ◽  
Author(s):  
Abdellah Bnouhachem ◽  
Muhammad Aslam Noor ◽  
Mohamed Khalfaoui ◽  
Sheng Zhaohan
Keyword(s):  
Complementarity Problems ◽  
Nonlinear Complementarity Problems ◽  
Proximal Method ◽  
Nonlinear Complementarity

An interior proximal method in vector optimization

2011 ◽  
Vol 214 (3) ◽  
pp. 485-492 ◽  
Author(s):  
Kely D.V. Villacorta ◽  
P. Roberto Oliveira
Keyword(s):  
Vector Optimization ◽  
Proximal Method

An improved proximal method with quasi-distance for nonconvex multiobjective optimization problem

2022 ◽  
Vol 0 (0) ◽  
Author(s):  
Fouzia Amir ◽  
Ali Farajzadeh ◽  
Jehad Alzabut
Keyword(s):  
Multiobjective Optimization ◽  
Optimization Problems ◽  
Optimal Solution ◽  
Convergence Result ◽  
Proximal Method ◽  
Pareto Solution ◽  
Multiobjective Optimization Problems ◽  
Locally Lipschitz ◽  
The Cost ◽  
Constrained Multiobjective Optimization

Abstract Multiobjective optimization is the optimization with several conflicting objective functions. However, it is generally tough to find an optimal solution that satisfies all objectives from a mathematical frame of reference. The main objective of this article is to present an improved proximal method involving quasi-distance for constrained multiobjective optimization problems under the locally Lipschitz condition of the cost function. An instigation to study the proximal method with quasi distances is due to its widespread applications of the quasi distances in computer theory. To study the convergence result, Fritz John’s necessary optimality condition for weak Pareto solution is used. The suitable conditions to guarantee that the cluster points of the generated sequences are Pareto–Clarke critical points are provided.

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