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A New Nonlinear Lagrangian Method for Nonconvex Semidefinite Programming
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Y. Li
Published/Copyright:
June 9, 2010
Abstract
We study convergence properties of a new nonlinear Lagrangian method for nonconvex semidefinite programming. The convergence analysis shows that this method converges locally when the penalty parameter is less than a threshold and the error bound of solution is proportional to the penalty parameter under the constraint nondegeneracy condition, the strict complementarity condition and the strong second order sufficient conditions. The major tools used in the analysis include the second implicit function theorem and differentials of Löwner operators.
Received: 2008-01-30
Revised: 2008-08-17
Published Online: 2010-06-09
Published in Print: 2009-December
© Heldermann Verlag
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- A New Nonlinear Lagrangian Method for Nonconvex Semidefinite Programming
- Blow-up for Semidiscretization of a Localized Semilinear Heat Equation
- Probability on Matrix-Cone Hypergroups: Limit Theorems and Structural Properties
- A System of Two Conservation Laws with Flux Conditions and Small Viscosity
- Sandwich Theorems for Certain Subclasses of Analytic Functions Defined by Family of Linear Operators
- Oscillation of Solutions of Second Order Neutral Differential Equations with Positive and Negative Coefficients
Keywords for this article
Semidefinite programming;
nonlinear Lagrangian method;
convergence analysis
Articles in the same Issue
- A New Nonlinear Lagrangian Method for Nonconvex Semidefinite Programming
- Blow-up for Semidiscretization of a Localized Semilinear Heat Equation
- Probability on Matrix-Cone Hypergroups: Limit Theorems and Structural Properties
- A System of Two Conservation Laws with Flux Conditions and Small Viscosity
- Sandwich Theorems for Certain Subclasses of Analytic Functions Defined by Family of Linear Operators
- Oscillation of Solutions of Second Order Neutral Differential Equations with Positive and Negative Coefficients
