On the convergence of augmented Lagrangian methods for nonlinear semidefinite programming

H. Luo (), H. Wu () and G. Chen ()

Journal of Global Optimization, 2012, vol. 54, issue 3, 599-618

Abstract: In this paper, we present new convergence properties of the augmented Lagrangian method for nonlinear semidefinite programs (NSDP). Convergence to the approximately global solutions and optimal values of NSDP is first established for a basic augmented Lagrangian scheme under mild conditions, without requiring the boundedness condition of the multipliers. We then propose four modified augmented Lagrangian methods for NSDP based on different algorithmic strategies. We show that the same convergence of the proposed methods can be ensured under weaker conditions. Copyright Springer Science+Business Media, LLC. 2012

Keywords: Nonlinear semidefinite program; Modified augmented Lagrangian methods; Convergence to an $${\epsilon}$$ -global solution; Boundedness of multipliers (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (6)

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DOI: 10.1007/s10898-011-9779-x

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