CGS algorithms for unconstrained minimization of functions

DOI10.1007/BF00935624zbMath0281.65043OpenAlexW2020837638WikidataQ98115593 ScholiaQ98115593MaRDI QIDQ1843296

E. H. Mookini, R. F. Dennemeyer

Publication date: 1975

Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf00935624

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30)

Related Items (6)

Convergence of the conjugate Gram-Schmidt method ⋮ Extensions of CGS algorithms: Generalized least-square solutions ⋮ CGS algorithms for constrained extremization of functions ⋮ Conjugate direction methods in non-Hilbert spaces ⋮ Numerical experience with conjugate direction methods in constrained minimization ⋮ A discrete Newton algorithm for minimizing a function of many variables

Cites Work

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• A Rapidly Convergent Descent Method for Minimization
• A Comparison of Several Current Optimization Methods, and the use of Transformations in Constrained Problems
• Methods of conjugate gradients for solving linear systems

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