Some investigations in a new algorithm for nonlinear optimization based on conic models of the objective function

DOI10.1007/BF00934743zbMath0521.49024MaRDI QIDQ1054998

Lucio Grandinetti

Publication date: 1984

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

zbMATH Keywords

unconstrained optimizationquasi-Newton algorithmscollinear scaling methodconic models

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Newton-type methods (49M15) Numerical methods based on nonlinear programming (49M37)

Related Items (11)

A new subspace minimization conjugate gradient method based on conic model for large-scale unconstrained optimization ⋮ A numerical evaluation of some collinear scaling algorithms for unconstrained ⋮ A model-hybrid approach for unconstrained optimization problems ⋮ A combined class of self-scaling and modified quasi-Newton methods ⋮ Damped techniques for the limited memory BFGS method for large-scale optimization ⋮ On the behaviour of a combined extra-updating/self-scaling BFGS method ⋮ Optimum and equilibrium in a transport problem with queue penalization effect ⋮ An adaptive conic trust-region method for unconstrained optimization ⋮ Wide interval for efficient self-scaling quasi-Newton algorithms ⋮ Extra updates for the bfgs method^∗ ⋮ Variational quasi-Newton methods for unconstrained optimization

Cites Work

• A variable metric-method for function minimization derived from invariancy to nonlinear scaling
• Numerical comparison of several variable metric algorithms
• Conic Approximations and Collinear Scalings for Optimizers
• On the Superlinear Convergence of an Algorithm for Solving a Sparse Minimization Problem
• The Q-Superlinear Convergence of a Collinear Scaling Algorithm for Unconstrained Optimization
• On the selection of parameters in Self Scaling Variable Metric Algorithms
• Self-Scaling Variable Metric (SSVM) Algorithms
• Optimally conditioned optimization algorithms without line searches
• Optimal conditioning of self-scaling variable Metric algorithms
• Quasi-Newton Methods, Motivation and Theory
• On Sparse and Symmetric Matrix Updating Subject to a Linear Equation
• A Characterization of Superlinear Convergence and Its Application to Quasi-Newton Methods
• Quasi-newton algorithms generate identical points
• Quasi-Newton Methods for Unconstrained Optimization
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