scholarly journals A limited-memory Riemannian symmetric rank-one trust-region method with an efficient algorithm for its subproblem

2021 ◽  
Vol 54 (9) ◽  
pp. 572-577
Author(s):  
Wen Huang ◽  
Kyle A. Gallivan
Keyword(s):  
Efficient Algorithm ◽  
Trust Region Method ◽  
Trust Region ◽  
Limited Memory ◽  
Region Method ◽  
Rank One ◽  
Symmetric Rank One

Analysis of a Symmetric Rank-One Trust Region Method

1996 ◽  
Vol 6 (4) ◽  
pp. 1025-1039 ◽  
Author(s):  
Richard H. Byrd ◽  
Humaid Fayez Khalfan ◽  
Robert B. Schnabel
Keyword(s):  
Trust Region Method ◽  
Trust Region ◽  
Region Method ◽  
Rank One ◽  
Symmetric Rank One

A Riemannian symmetric rank-one trust-region method

2014 ◽  
Vol 150 (2) ◽  
pp. 179-216 ◽  
Author(s):  
Wen Huang ◽  
P.-A. Absil ◽  
K. A. Gallivan
Keyword(s):  
Trust Region Method ◽  
Trust Region ◽  
Region Method ◽  
Rank One ◽  
Symmetric Rank One

A Riemannian subspace limited-memory SR1 trust region method

2015 ◽  
Vol 10 (8) ◽  
pp. 1705-1723 ◽  
Author(s):  
Hejie Wei ◽  
Wei Hong Yang
Keyword(s):  
Trust Region Method ◽  
Trust Region ◽  
Limited Memory ◽  
Region Method

Based on GA Mixed with Trust Region Method Solving Nonlinear Least Square Problems

2011 ◽  
Vol 141 ◽  
pp. 92-97
Author(s):  
Miao Hu ◽  
Tai Yong Wang ◽  
Bo Geng ◽  
Qi Chen Wang ◽  
Dian Peng Li
Keyword(s):  
Genetic Algorithm ◽  
Optimization Problems ◽  
Trust Region Method ◽  
Trust Region ◽  
Least Square ◽  
Search Range ◽  
Genetic Search ◽  
Region Method ◽  
Unconstrained Optimization Problems ◽  
Least Square Problems

Nonlinear least square is one of the unconstrained optimization problems. In order to solve the least square trust region sub-problem, a genetic algorithm (GA) of global convergence was applied, and the premature convergence of genetic algorithms was also overcome through optimizing the search range of GA with trust region method (TRM), and the convergence rate of genetic algorithm was increased by the randomness of the genetic search. Finally, an example of banana function was established to verify the GA, and the results show the practicability and precision of this algorithm.

A BFGS trust-region method for nonlinear equations

Computing ◽  
2011 ◽  
Vol 92 (4) ◽  
pp. 317-333 ◽  
Author(s):  
Gonglin Yuan ◽  
Zengxin Wei ◽  
Xiwen Lu
Keyword(s):  
Nonlinear Equations ◽  
Trust Region Method ◽  
Trust Region ◽  
Region Method
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