A subgradient-like algorithm for solving vector convex inequalities
From MaRDI portal
Publication:467438
DOI10.1007/s10957-013-0300-1zbMath1306.90141OpenAlexW2044746947MaRDI QIDQ467438
Publication date: 3 November 2014
Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10957-013-0300-1
Related Items
A proximal gradient splitting method for solving convex vector optimization problems, Subgradient algorithms for solving variable inequalities, On inexact projected gradient methods for solving variable vector optimization problems, A strongly convergent proximal point method for vector optimization
Cites Work
- Unnamed Item
- Unnamed Item
- Convergence of the projected gradient method for quasiconvex multiobjective optimization
- Convergence of direct methods for paramonotone variational inequalities
- Functional analysis, Sobolev spaces and partial differential equations
- Scalarization of vector optimization problems
- Convex vector functions and their subdifferential
- On the projected subgradient method for nonsmooth convex optimization in a Hilbert space
- System modelling and optimization. Proceedings of the 16th IFIP-TC7 conference, Compiègne, France, July 5-9, 1993
- Approximate efficiency and scalar stationarity in unbounded nonsmooth convex vector optimization problems
- Forcing strong convergence of proximal point iterations in a Hilbert space
- On the choice of parameters for the weighting method in vector optimization
- Vector Optimization Problems and Their Solution Concepts
- A Strongly Convergent Method for Nonsmooth Convex Minimization in Hilbert Spaces
- Scalarization in vector optimization
- Introduction to the Theory of Nonlinear Optimization
- A vector variational inequality and optimization over an efficient set
- A Strongly Convergent Direct Method for Monotone Variational Inequalities in Hilbert Spaces
- A Mesh-Independence Principle for Operator Equations and Their Discretizations
- Application of the Mesh Independence Principle to Mesh Refinement Strategies
- Newton's Mesh Independence Principle for a Class Of Optimal Shape Design Problems
- On Projection Algorithms for Solving Convex Feasibility Problems
- Iterative Algorithms for Equilibrium Problems
- Block-Iterative Algorithms with Underrelaxed Bregman Projections
- Reconstruction of pictures from their projections
- Minimization of unsmooth functionals
- A Weak-to-Strong Convergence Principle for Fejér-Monotone Methods in Hilbert Spaces
- Functional Operators (AM-22), Volume 2
