In this paper a numerical comparison between many of these methods is performed using all the suitable problems of the CUTE collection.
Augmented Lagrangian algorithms are very popular tools for solving nonlinear programming problems. At each outer iteration of these methods a simpler ...
Jul 7, 2003 · Abstract. Augmented Lagrangian algorithms are very popular tools for solving nonlinear program- ming problems. At each outer iteration of ...
Abstract. Augmented Lagrangian algorithms are very popular tools for solving nonlinear programming prob- lems. At each outer iteration of these methods a ...
Numerical Comparison of Augmented Lagrangian Algorithms ... - ProQuest
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In this paper a numerical comparison between many of these methods is performed using all the suitable problems of the CUTE collection.
While the popular augmented Lagrangian method may produce more difficult nonconvex problems due to the nonlinearity of constraints. View. Show abstract.
NUMERICAL TESTS ON THE ADAPTIVE AL METHODS the problems, the number of iterations required by the algorithm was less than or equal to α times the number of ...
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Problems with such generality present grand difficulties: they are nonconvex and nonsmooth, they feature complex geometries, qualification conditions and other ...
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On the nonconvex problems, BSG significantly outperformed the deterministic BCD method because the latter tends to stagnate early near local minimizers. Overall ...
We consider the well-known augmented Lagrangian method for constrained optimization and compare its classical variant to a modified counterpart which uses ...