PREDICTOR–CORRECTOR SMOOTHING NEWTON METHOD FOR SOLVING SEMIDEFINITE PROGRAMMING

DOI10.1017/S0004972708001214zbMath1173.90499OpenAlexW2124136467MaRDI QIDQ3633327

Caiying Wu, Guo-Qing Chen

Publication date: 18 June 2009

Published in: Bulletin of the Australian Mathematical Society (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1017/s0004972708001214

zbMATH Keywords

semidefinite programmingsuperlinear convergenceFischer-Burmeister functionsemidefinite complementarity

Mathematics Subject Classification ID

Semidefinite programming (90C22)

Cites Work

• Non-interior continuation methods for solving semidefinite complementarity problems
• Superlinear/quadratic one-step smoothing Newton method for \(P_0\)-NCP without strict complementarity
• A nonsmooth version of Newton's method
• Superlinear/quadratic one-step smoothing Newton method for \(P_0\)-NCP
• Solving Some Large Scale Semidefinite Programs via the Conjugate Residual Method
• Interior-Point Methods for the Monotone Semidefinite Linear Complementarity Problem in Symmetric Matrices
• Matrix Analysis
• Primal-Dual Interior-Point Methods for Semidefinite Programming: Convergence Rates, Stability and Numerical Results
• Primal--Dual Path-Following Algorithms for Semidefinite Programming
• On Extending Some Primal--Dual Interior-Point Algorithms From Linear Programming to Semidefinite Programming
• Semidefinite Programming in the Space of Partial Positive Semidefinite Matrices
• Solving Large Scale Semidefinite Programs via an Iterative Solver on the Augmented Systems
• Semidefinite Programs: New Search Directions, Smoothing-Type Methods, and Numerical Results
• An Interior-Point Method for Semidefinite Programming

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