Interpolation by conic model for unconstrained optimization
type: Item
instance of: scholarly article
title: Interpolation by conic model for unconstrained optimization
zbMATH Open document ID: 0815.65085
DOI: 10.1007/BF02238081
author: V. Pereyra
published in: Computing
publication date: 1995-01-30T00:00:00Z
review text: A combination of quasi-Newton methods with conic functions for solving unconstrained optimization problems is described. The method is q- superlinearly convergent, and decreases the number of line searches. Numerical examples show that the new method is successful.
Mathematics Subject Classification ID: 65K05
Mathematics Subject Classification ID: 90C30
zbMATH DE Number: 714645
zbMATH Keywords: conic model
zbMATH Keywords: q-superlinear convergence
zbMATH Keywords: numerical examples
zbMATH Keywords: quasi-Newton methods
zbMATH Keywords: conic functions
zbMATH Keywords: unconstrained optimization
zbMATH Keywords: line searches
reviewed by: Horst Hollatz
describes a project that uses: minpack
MaRDI profile type: Publication
cites work: Deriving collinear scaling algorithms as extensions of quasi-Newton methods and the local convergence of DFP- and BFGS-related collinear scaling algorithms
cites work: On the Local and Superlinear Convergence of Quasi-Newton Methods
cites work: Conic Approximations and Collinear Scalings for Optimizers
cites work: Quasi-Newton Methods, Motivation and Theory
cites work: Q3702408
cites work: A Characterization of Superlinear Convergence and Its Application to Quasi-Newton Methods
cites work: A Conic Algorithm for Optimization
cites work: Testing Unconstrained Optimization Software
cites work: Q4399582
cites work: The Q-Superlinear Convergence of a Collinear Scaling Algorithm for Unconstrained Optimization
cites work: Q4018587
full work available at URL: https://doi.org/10.1007/bf02238081
OpenAlex ID: W1485035947
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description: scientific article; zbMATH DE number 714645