On a modified subgradient algorithm for dual problems via sharp augmented lagrangian

dc.contributor.author	Burachik, R.S.
dc.contributor.author	Gasimov, R.
dc.contributor.author	Ismayilova, N.
dc.contributor.author	Kaya, C.Y.
dc.date.issued	2006
dc.description.abstract	We study convergence properties of a modified subgradient algorithm, applied to the dual problem defined by the sharp augmented Lagrangian. The primal problem we consider is nonconvex and nondifferentiable, with equality constraints. We obtain primal and dual convergence results, as well as a condition for existence of a dual solution. Using a practical selection of the step-size parameters, we demonstrate the algorithm and its advantages on test problems, including an integer programming and an optimal control problem.
dc.identifier.citation	Journal of Global Optimization, 2006; 34(1):55-78
dc.identifier.doi	10.1007/s10898-005-3270-5
dc.identifier.issn	0925-5001
dc.identifier.issn	1573-2916
dc.identifier.uri	https://hdl.handle.net/1959.8/87551
dc.language.iso	en
dc.publisher	Springer
dc.rights	Copyright 2006 Springer
dc.source.uri	https://doi.org/10.1007/s10898-005-3270-5
dc.subject	Augmented Lagradgian
dc.subject	Nonconvex programming
dc.subject	Nonsmooth optimization
dc.subject	Sharp Lagrangian
dc.subject	Subgradient optimization
dc.title	On a modified subgradient algorithm for dual problems via sharp augmented lagrangian
dc.type	Journal article
pubs.publication-status	Published
ror.fileinfo	12142964860001831 13142962980001831 9915914141701831_53109902180001831.pdf
ror.mmsid	9915914141701831

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