Kernel-function Based Algorithms for Semidefinite Optimization

DOI10.1051/ro/2009011zbMath1170.90455OpenAlexW2161659241MaRDI QIDQ3632808

M. El Ghami, Cornelis Roos, Yan-Qin Bai

Publication date: 12 June 2009

Published in: RAIRO - Operations Research (Search for Journal in Brave)

Full work available at URL: https://eudml.org/doc/105428

zbMATH Keywords

complexityprimal-dual methodinterior-point methods

Mathematics Subject Classification ID

Semidefinite programming (90C22) Sensitivity, stability, parametric optimization (90C31)

Related Items

Kernel-function-based primal-dual interior-point methods for convex quadratic optimization over symmetric cone, A large-update feasible interior-point algorithm for convex quadratic semi-definite optimization based on a new kernel function, Complexity of primal-dual interior-point algorithm for linear programming based on a new class of kernel functions, A unified kernel function approach to primal-dual interior-point algorithms for convex quadratic SDO, A new primal-dual interior-point method for semidefinite optimization based on a parameterized kernel function, Primal-dual interior-point algorithm for semidefinite optimization based on a new kernel function with trigonometric barrier term, Kernel-function Based Primal-Dual Algorithms forP_*(κ) Linear Complementarity Problems, Self-Regular Interior-Point Methods for Semidefinite Optimization

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