Structured minimal-memory inexact quasi-Newton method and secant preconditioners for augmented Lagrangian optimization
Author:
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Computational Mathematics,Control and Optimization
Link
http://link.springer.com/content/pdf/10.1007/s10589-007-9050-z.pdf
Reference47 articles.
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2. Andreani, R., Birgin, E.G., Martínez, J.M., Schuverdt, M.L.: On Augmented Lagrangian methods with general lower-level constraints. SIAM J. Optim. (2007, in press)
3. Andreani, R., Martínez, J.M., Schuverdt, M.L.: On the relation between the constant positive linear dependence condition and quasinormality constraint qualification. J. Optim. Theory Appl. 125, 473–485 (2005)
4. Barzilai, J., Borwein, J.M.: Two point step size gradient methods. IMA J. Numer. Anal. 8, 141–148 (1988)
5. Birgin, E.G., Castillo, R., Martínez, J.M.: Numerical comparison of Augmented Lagrangian algorithms for nonconvex problems. Comput. Optim. Appl. 31, 31–56 (2005)
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