A Second-Order Bundle Method Based on -Decomposition Strategy for a Special Class of Eigenvalue Optimizations

DOI10.1080/01630563.2016.1138969zbMath1352.65152OpenAlexW2462358129MaRDI QIDQ3188440

Li-Ping Pang, Ming Huang, Xi-Jun Liang, Fan-Yun Meng

Publication date: 19 August 2016

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

Full work available at URL: https://doi.org/10.1080/01630563.2016.1138969

zbMATH Keywords

algorithmnumerical exampleglobal convergencenonsmooth optimizationeigenvalue optimizationnonconvex optimizationlocal quadratic convergenceD.C. function\(\mathcal U\)-Lagrangian \(\mathcal{UV}\)-decompositionsecond-order proximal bundle method

Mathematics Subject Classification ID

Numerical computation of eigenvalues and eigenvectors of matrices (65F15) Numerical mathematical programming methods (65K05) Nonconvex programming, global optimization (90C26)

Related Items

A redistributed proximal bundle method for nonsmooth nonconvex functions with inexact information, The space decomposition method for the sum of nonlinear convex maximum eigenvalues and its applications, \(\mathcal{UV}\)-theory of a class of semidefinite programming and its applications, On Solving the Convex Semi-Infinite Minimax Problems via Superlinear 𝒱𝒰 Incremental Bundle Technique with Partial Inexact Oracle

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