An Interior Point Constrained Trust Region Method for a Special Class of Nonlinear Semidefinite Programming Problems

2002 ◽  
Vol 12 (4) ◽  
pp. 1048-1074 ◽  
Author(s):  
F. Leibfritz ◽  
E. M. E. Mostafa
2000 ◽  
Vol 89 (1) ◽  
pp. 149-185 ◽  
Author(s):  
Richard H. Byrd ◽  
Jean Charles Gilbert ◽  
Jorge Nocedal

2011 ◽  
Vol 141 ◽  
pp. 92-97
Author(s):  
Miao Hu ◽  
Tai Yong Wang ◽  
Bo Geng ◽  
Qi Chen Wang ◽  
Dian Peng Li

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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