A large-update interior-point algorithm for convex quadratic semi-definite optimization based on a new kernel function

DOI10.1007/s10114-012-0194-0zbMath1254.90158OpenAlexW2115035264MaRDI QIDQ1928163

Ming Wang Zhang

Publication date: 2 January 2013

Published in: Acta Mathematica Sinica. English Series (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10114-012-0194-0

zbMATH Keywords

complexitykernel functioninterior-point algorithmlarge-update methodconvex quadratic semi-definite optimization

Mathematics Subject Classification ID

Semidefinite programming (90C22) Convex programming (90C25) Complementarity and equilibrium problems and variational inequalities (finite dimensions) (aspects of mathematical programming) (90C33)

Related Items (6)

A large-update feasible interior-point algorithm for convex quadratic semi-definite optimization based on a new kernel function ⋮ Unnamed Item ⋮ A unified complexity analysis of interior point methods for semidefinite problems based on trigonometric kernel functions ⋮ An efficient parameterized logarithmic kernel function for semidefinite optimization ⋮ Complexity analysis of primal-dual interior-point methods for semidefinite optimization based on a parametric kernel function with a trigonometric barrier term ⋮ Novel kernel function with a hyperbolic barrier term to primal-dual interior point algorithm for SDP problems

Cites Work

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