A Proximal-Type Method for Convex Vector Optimization Problem in Banach Spaces

DOI10.1080/01630560902735272zbMath1167.90617OpenAlexW2025487344MaRDI QIDQ3615534

Ke Quan Zhao, Zhe Chen

Publication date: 20 March 2009

Published in: Numerical Functional Analysis and Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/01630560902735272

zbMATH Keywords

vector optimizationBanach spacesLyapunov functionalweak Pareto optimal solutionproximal-type methodweakly converge

Mathematics Subject Classification ID

Convex programming (90C25) Multi-objective and goal programming (90C29) Programming in abstract spaces (90C48)

Related Items (6)

Generalized proximal-type methods for weak vector variational inequality problems in Banach spaces ⋮ Generalized Proximal Method for Efficient Solutions in Vector Optimization ⋮ Logarithmic-Barrier Decomposition Interior-Point Methods for Stochastic Linear Optimization in a Hilbert Space ⋮ Generalized proximal point algorithms for multiobjective optimization problems ⋮ Generalized viscosity approximation methods in multiobjective optimization problems ⋮ Inexact proximal point methods in metric spaces

Cites Work

• Calmness and exact penalization in vector optimization with cone constraints
• Steepest descent methods for multicriteria optimization.
• A projected gradient method for vector optimization problems
• Approximate proximal methods in vector optimization
• Vector optimization. Set-valued and variational analysis.
• A Proximal Point Method for the Variational Inequality Problem in Banach Spaces
• Nonlinear Ill-posed Problems of Monotone Type
• On the Convergence of the Proximal Point Algorithm for Convex Minimization
• Monotone Operators and the Proximal Point Algorithm
• Strong Convergence of a Proximal-Type Algorithm in a Banach Space
• Proximal Methods in Vector Optimization
• Local Convergence of the Proximal Point Algorithm and Multiplier Methods Without Monotonicity
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