scholarly journals The global and superlinear convergence of a new nonmonotone MBFGS algorithm on convex objective functions

2008 ◽  
Vol 220 (1-2) ◽  
pp. 422-438 ◽  
Author(s):  
Liying Liu ◽  
Shengwei Yao ◽  
Zengxin Wei
2011 ◽  
Vol 18 (9) ◽  
pp. 1303-1309 ◽  
Author(s):  
Zhaocheng Cui ◽  
Boying Wu

In this paper, we propose a new self-adaptive trust region method for unconstrained optimization problems and develop some convergence properties. In our algorithm, we use the previous and current iterative information to define a suitable trust region radius at each iteration. The global and superlinear convergence properties of the algorithm are established under reasonable assumptions. Preliminary numerical results show that the new method is efficient and attractive for solving unconstrained optimization problems.


Computing ◽  
1982 ◽  
Vol 29 (4) ◽  
pp. 289-307 ◽  
Author(s):  
H. Kleinmichel ◽  
C. Richter ◽  
K. Schönefeld

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