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Numerical methods for large-scale nonlinear optimization

Published online by Cambridge University Press:  19 April 2005

Nick Gould ,
Dominique Orban  and
Philippe Toint
Nick Gould
Affiliation:
Computational Science and Engineering Department, Rutherford Appleton Laboratory, Chilton, Oxfordshire, England, E-mail: n.i.m.gould@rl.ac.uk
Dominique Orban
Affiliation:
Department of Mathematics and Industrial Engineering, Ecole Polytechnique de Montréal, 2900, Bd E. Montpetit, H3T 1J4 Montréal, Canada, E-mail: dominique.orban@polymtl.ca
Philippe Toint
Affiliation:
Department of Mathematics, University of Namur, 61, rue de Bruxelles, B-5000 Namur, Belgium, E-mail: philippe.toint@fundp.ac.be
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Abstract

Recent developments in numerical methods for solving large differentiable nonlinear optimization problems are reviewed. State-of-the-art algorithms for solving unconstrained, bound-constrained, linearly constrained and non-linearly constrained problems are discussed. As well as important conceptual advances and theoretical aspects, emphasis is also placed on more practical issues, such as software availability.

Type
Research Article
Information
Acta Numerica , Volume 14 , May 2005 , pp. 299 - 361
Copyright
© 2005 Cambridge University Press

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