Numerical methods for large-scale nonlinear optimization

N. Gould; Dominique Orban; P. Toint

doi:10.1017/S0962492904000248

Numerical methods for large-scale nonlinear optimization

N. Gould, Dominique Orban, P. Toint

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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 nonlinearly 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. © Cambridge University Press, 2005.

Original language	English
Pages (from-to)	299-361
Number of pages	63
Journal	Acta Numerica
Volume	14
DOIs	https://doi.org/10.1017/S0962492904000248
Publication status	Published - 1 Jan 2005

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10.1017/S0962492904000248

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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 nonlinearly 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. {\textcopyright} Cambridge University Press, 2005.",

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Numerical methods for large-scale nonlinear optimization

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ADALGOPT: ADALGOPT - Advanced algorithms in nonlinear optimization

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Numerical methods for large-scale nonlinear optimization

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ADALGOPT: ADALGOPT - Advanced algorithms in nonlinear optimization

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