scholarly journals A quasi-Newton trust region method based on a new fractional model

2015 ◽  
Vol 5 (3) ◽  
pp. 237-249 ◽  
Author(s):  
Honglan Zhu ◽  
◽  
Qin Ni ◽  
Meilan Zeng ◽  
Keyword(s):  
Trust Region Method ◽  
Trust Region ◽  
Fractional Model ◽  
Region Method ◽  
Quasi Newton

scholarly journals A Fractional Trust Region Method for Linear Equality Constrained Optimization

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Honglan Zhu ◽  
Qin Ni ◽  
Liwei Zhang ◽  
Weiwei Yang
Keyword(s):  
Constrained Optimization ◽  
Optimization Problems ◽  
Null Space ◽  
Trust Region Method ◽  
Trust Region ◽  
Test Problems ◽  
Fractional Model ◽  
Region Method ◽  
Linear Equality ◽  
Space Technique

A quasi-Newton trust region method with a new fractional model for linearly constrained optimization problems is proposed. We delete linear equality constraints by using null space technique. The fractional trust region subproblem is solved by a simple dogleg method. The global convergence of the proposed algorithm is established and proved. Numerical results for test problems show the efficiency of the trust region method with new fractional model. These results give the base of further research on nonlinear optimization.

A trust region method based on the fractional model for unconstrained optimization

2018 ◽  
Vol 48 (4) ◽  
pp. 531 ◽  
Author(s):  
Zhu Honglan ◽  
Ni Qin ◽  
Dang Changyin ◽  
Zhang Hao
Keyword(s):  
Unconstrained Optimization ◽  
Trust Region Method ◽  
Trust Region ◽  
Fractional Model ◽  
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.

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