A second-order convergence augmented Lagrangian method using non-quadratic penalty functions View Full Text


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Article Info

DATE

2019-03-12

AUTHORS

M. D. Sánchez, M. L. Schuverdt

ABSTRACT

The purpose of the present paper is to study the global convergence of a practical Augmented Lagrangian model algorithm that considers non-quadratic Penalty–Lagrangian functions. We analyze the convergence of the model algorithm to points that satisfy the Karush–Kuhn–Tucker conditions and also the weak second-order necessary optimality condition. The generation scheme of the Penalty–Lagrangian functions includes the exponential penalty function and the logarithmic-barrier without using convex information. More... »

PAGES

1-19

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s12597-019-00366-3

DOI

http://dx.doi.org/10.1007/s12597-019-00366-3

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1112703568


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