Hybrid proximal linearized algorithm for the split DC program in infinite-dimensional real Hilbert spaces

DOI10.1186/s13660-018-1840-6zbMath1498.90164OpenAlexW2889936000WikidataQ58706012 ScholiaQ58706012MaRDI QIDQ824790

Pei-Jung Yang, Chih-Sheng Chuang

Publication date: 15 December 2021

Published in: Journal of Inequalities and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1186/s13660-018-1840-6

zbMATH Keywords

critical pointsubdifferentialDC functionstrongly monotonicity

Mathematics Subject Classification ID

Nonconvex programming, global optimization (90C26) Optimality conditions and duality in mathematical programming (90C46) Programming in abstract spaces (90C48) Semi-infinite programming (90C34)

Cites Work

• Global convergence of a proximal linearized algorithm for difference of convex functions
• Lagrange-type duality in DC programming
• Local and global optimality conditions for dc infinite optimization problems
• Totally convex functions for fixed points computation and infinite dimensional optimization
• Convergence of generalized proximal point algorithms
• The DC (Difference of convex functions) programming and DCA revisited with DC models of real world nonconvex optimization problems
• Optimality conditions for DC programming problems with reverse convex constraints
• Lagrange duality in canonical DC programming
• Extended Farkas lemma and strong duality for composite optimization problems with DC functions
• Stable and Total Fenchel Duality for DC Optimization Problems in Locally Convex Spaces
• Two simple relaxed perturbed extragradient methods for solving variational inequalities in Euclidean spaces
• FIXED-POINT THEOREMS FOR NONCOMPACT MAPPINGS IN HILBERT SPACE
• Convex analysis and monotone operator theory in Hilbert spaces
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item