A class of polynomial primal-dual interior-point algorithms for semidefinite optimization

DOI10.1007/s11741-006-0114-6zbMath1208.90132OpenAlexW2067661291MaRDI QIDQ3415567

Guo-Qiang Wang, Yan-Qin Bai

Publication date: 19 January 2007

Published in: Journal of Shanghai University (English Edition) (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11741-006-0114-6

zbMATH Keywords

polynomial complexityprimal-dual interior-point methodslarge- and small-update methodssemidefinite optimization (SDO)

Mathematics Subject Classification ID

Semidefinite programming (90C22) Interior-point methods (90C51)

Related Items (5)

A new primal-dual interior-point algorithm for convex quadratic optimization ⋮ A unified complexity analysis of interior point methods for semidefinite problems based on trigonometric kernel functions ⋮ Penalized interior point approach for constrained nonlinear programming ⋮ Reduction of truss topology optimization ⋮ An efficient parameterized logarithmic kernel function for semidefinite optimization

Cites Work

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• Primal-dual interior-point algorithms for semidefinite optimization based on a simple kernel function
• Self-Scaled Barriers and Interior-Point Methods for Convex Programming
• Primal-Dual Interior-Point Methods for Self-Scaled Cones
• A Comparative Study of Kernel Functions for Primal-Dual Interior-Point Algorithms in Linear Optimization
• Handbook of semidefinite programming. Theory, algorithms, and applications

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