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Numerical methods for large-scale nonlinear optimization

Published online by Cambridge University Press:  19 April 2005

Nick Gould
Affiliation:
Computational Science and Engineering Department, Rutherford Appleton Laboratory, Chilton, Oxfordshire, England, E-mail: [email protected]
Dominique Orban
Affiliation:
Department of Mathematics and Industrial Engineering, Ecole Polytechnique de Montréal, 2900, Bd E. Montpetit, H3T 1J4 Montréal, Canada, E-mail: [email protected]
Philippe Toint
Affiliation:
Department of Mathematics, University of Namur, 61, rue de Bruxelles, B-5000 Namur, Belgium, E-mail: [email protected]

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
Copyright
© 2005 Cambridge University Press

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