Title
A Globally and Superlinearly Convergent Gauss--Newton-Based BFGS Method for Symmetric Nonlinear Equations
Abstract
In this paper, we present a Gauss--Newton-based BFGS method for solving symmetric nonlinear equations which contain, as a special case, an unconstrained optimization problem, a saddle point problem, and an equality constrained optimization problem. A suitable line search is proposed with which the presented BFGS method exhibits an approximate norm descent property. Under appropriate conditions, global convergence and superlinear convergence of the method are established. The numerical results show that the proposed method is successful.
Year
DOI
Venue
1999
10.1137/S0036142998335704
SIAM J. Numerical Analysis
Keywords
Field
DocType
symmetric nonlinear equations,saddle point problem,superlinearly convergent gauss,bfgs method,newton-based bfgs method,global convergence,optimization problem,superlinear convergence,appropriate condition,unconstrained optimization problem,approximate norm descent property,nonlinear equation
Quasi-Newton method,Mathematical optimization,Nonlinear system,Mathematical analysis,Lagrange multiplier,Line search,Broyden–Fletcher–Goldfarb–Shanno algorithm,Optimization problem,Mathematics,Gauss–Seidel method,Newton's method
Journal
Volume
Issue
ISSN
37
1
0036-1429
Citations 
PageRank 
References 
42
4.81
1
Authors
2
Name
Order
Citations
PageRank
Donghui Li138032.40
Masao Fukushima22050172.73