A general iterative method for solving constrained convex minimization problems

DOI10.1007/s10957-013-0413-6zbMath1298.90073OpenAlexW1991274744MaRDI QIDQ467418

Min-Min Li, Ming Tian

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/s10957-013-0413-6

zbMATH Keywords

fixed pointvariational inequalitynonexpansive mappingsconstrained convex minimizationregularization algorithmaveraged mapping

Mathematics Subject Classification ID

Convex programming (90C25) Complementarity and equilibrium problems and variational inequalities (finite dimensions) (aspects of mathematical programming) (90C33) Programming in abstract spaces (90C48)

Cites Work

• Averaged mappings and the gradient-projection algorithm
• A general iterative algorithm for nonexpansive mappings in Hilbert spaces
• A hybrid approximation method for equilibrium and fixed point problems for a monotone mapping and a nonexpansive mapping
• Strong convergence of composite iterative methods for equilibrium problems and fixed point problems
• A multiprojection algorithm using Bregman projections in a product space
• Iterative methods for the split feasibility problem in infinite-dimensional Hilbert spaces
• Iterative methods for finding minimum-norm fixed points of nonexpansive mappings with applications
• A variable Krasnosel'skii–Mann algorithm and the multiple-set split feasibility problem
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