An efficient parameterized logarithmic kernel function for semidefinite optimization
type: Item
instance of: scholarly article
title: An efficient parameterized logarithmic kernel function for semidefinite optimization
zbMATH Open document ID: 1466.90066
author: Louiza Derbal
author: Zakia Kebbiche
published in: Acta Mathematicae Applicatae Sinica. English Series
publication date: 2021-05-03T00:00:00Z
Mathematics Subject Classification ID: 90C22
Mathematics Subject Classification ID: 90C31
Mathematics Subject Classification ID: 90C51
zbMATH DE Number: 7342573
zbMATH Keywords: kernel function
zbMATH Keywords: interior-point algorithms
zbMATH Keywords: semidefinite optimization
zbMATH Keywords: complexity bound
zbMATH Keywords: primal-dual methods
MaRDI profile type: Publication
full work available at URL: s10255-020-0955-y
OpenAlex ID: W3082995987
cites work: Interior Point Methods in Semidefinite Programming with Applications to Combinatorial Optimization
cites work: A new proximity function generating the best known iteration bounds for both large-update and small-update interior-point methods
cites work: A New Efficient Large-Update Primal-Dual Interior-Point Method Based on a Finite Barrier
cites work: A Comparative Study of Kernel Functions for Primal-Dual Interior-Point Algorithms in Linear Optimization
cites work: A class of large-update and small-update primal-dual interior-point algorithms for linear optimization
cites work: Q5144448
cites work: On complexity analysis of the primal-dual interior-point method for semidefinite optimization problem based on a new proximity function
cites work: Aspects of semidefinite programming. Interior point algorithms and selected applications
cites work: Theoretical and Numerical Result for Linear Optimization Problem Based on a New Kernel Function
cites work: Interior-point methods for linear optimization based on a kernel function with a trigonometric barrier term
cites work: Interior-Point Methods for the Monotone Semidefinite Linear Complementarity Problem in Symmetric Matrices
cites work: A new kind of simple kennel function yielding good iteration bounds for primal-dual interior-point methods
cites work: Q4324980
cites work: Self-regular functions and new search directions for linear and semidefinite optimization
cites work: Q4791754
cites work: Complexity analysis of an interior-point algorithm for linear optimization based on a new proximity function
cites work: Complexity of interior-point methods for linear optimization based on a new trigonometric kernel function
cites work: Q4339096
cites work: Symmetric primal-dual path-following algorithms for semidefinite programming
cites work: On the Nesterov--Todd Direction in Semidefinite Programming
cites work: A study of search directions in primal-dual interior-point methods for semidefinite programming
cites work: A class of polynomial primal-dual interior-point algorithms for semidefinite optimization
cites work: Full Nesterov–Todd step feasible interior-point method for the CartesianP*(κ)-SCLCP
cites work: Primal-dual interior-point algorithms for semidefinite optimization based on a simple kernel function
cites work: Handbook of semidefinite programming. Theory, algorithms, and applications
cites work: A large-update interior-point algorithm for convex quadratic semi-definite optimization based on a new kernel function
cites work: On Extending Some Primal--Dual Interior-Point Algorithms From Linear Programming to Semidefinite Programming
DOI: 10.1007/S10255-020-0955-Y
description: scientific article; zbMATH DE number 7342573