A decomposition method with redistributed subroutine for constrained nonconvex optimization

DOI10.1155/2013/376403zbMath1270.90050OpenAlexW2003277551WikidataQ58916088 ScholiaQ58916088MaRDI QIDQ1949452

Yuan Lu, Dan Li, Li-Ping Pang, Wei Wang

Publication date: 8 May 2013

Published in: Abstract and Applied Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2013/376403

zbMATH Keywords

piecewise \(C^2\) objectivessmooth inequality constraintssuperlinear convergent \(\mathcal{VU}\)-algorithm

Mathematics Subject Classification ID

Nonconvex programming, global optimization (90C26)

Cites Work

• A decomposition algorithm for convex nondifferentiable minimization with errors
• A proximal method for identifying active manifolds
• A \(\mathcal{UV}\)-decomposed method for solving an MPEC problem
• Computing proximal points of nonconvex functions
• A superlinear space decomposition algorithm for constrained nonsmooth convex program
• Properties of the Moreau-Yosida regularization of a piecewise \(C^2\) convex function
• Functions and sets of smooth substructure: relationships and examples
• A \(\mathcal{VU}\)-algorithm for convex minimization
• On $\mathcalVU$-theory for Functions with Primal-Dual Gradient Structure
• A Redistributed Proximal Bundle Method for Nonconvex Optimization
• Identifying Structure of Nonsmooth Convex Functions by the Bundle Technique
• Variational Analysis
• Primal-Dual Gradient Structured Functions: Second-Order Results; Links to Epi-Derivatives and Partly Smooth Functions
• 𝒱𝒰-smoothness and proximal point results for some nonconvex functions
• The 𝒰-Lagrangian of a convex function
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