Convergence Properties of Algorithms for Nonlinear Optimization

This paper reviews some of the most successful methods for unconstrained, constrained and nondifferentiable optimization calculations. Particular attention is given to the contribution that theoretical analysis has made to the development of algorithms. It seems that practical considerations provide...

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Bibliographic Details
Published inSIAM review Vol. 28; no. 4; pp. 487 - 500
Main Author Powell, M. J. D.
Format Journal Article
LanguageEnglish
Published Philadelphia, PA The Society for Industrial and Applied Mathematics 01.12.1986
Society for Industrial and Applied Mathematics
Subjects
Algorithms
Applied mathematics
Approximation
Conjugate gradient method
Constrained optimization
Differentiable functions
Exact sciences and technology
Mathematical functions
Mathematics
Matrices
Methods
Numerical analysis
Numerical analysis. Scientific computation
Numerical approximation
Objective functions
Optimization
Quadratic functions
Sciences and techniques of general use
Approximation
Unconstrained optimization
Algorithm
Optimization
Convergence
Constrained optimization
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Summary:This paper reviews some of the most successful methods for unconstrained, constrained and nondifferentiable optimization calculations. Particular attention is given to the contribution that theoretical analysis has made to the development of algorithms. It seems that practical considerations provide the main new ideas, and that subsequent theoretical studies give improvements to algorithms, coherence to the subject, and better understanding.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
content type line 14
ISSN:0036-1445
1095-7200
DOI:10.1137/1028154