Abstract
A method for minimizing a convex continuously differentiable function of two variables was proposed in [1], where it was shown that its rate of convergence is geometric with coefficient 0.9543. We shall describe two modifications of this method with improved convergence rates.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
V.F. Demyanov. “On minimizing a convex function on a plane”, Zh. Vychisl. Mat. Mat. Fiz. 16 (1) (1976) 247–251.
D.J. Wilde. Optimum Seeking Methods. Prentice-Hall Intern. Series in the Physical and Chemical Engineering Sciences, Prentice-Hall, Englewood Cliffs, N.J., 1964.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1985 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Paizerova, F.A. (1985). An Accelerated Method for Minimizing a Convex Function of Two Variables. In: Demyanov, V.F., Pallaschke, D. (eds) Nondifferentiable Optimization: Motivations and Applications. Lecture Notes in Economics and Mathematical Systems, vol 255. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-12603-5_22
Download citation
DOI: https://doi.org/10.1007/978-3-662-12603-5_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-15979-7
Online ISBN: 978-3-662-12603-5
eBook Packages: Springer Book Archive