A general asymptotic function with applications in nonconvex optimization

2020 ◽  
Vol 78 (1) ◽  
pp. 49-68
Author(s):  
Nicolas Hadjisavvas ◽  
Felipe Lara ◽  
Dinh The Luc
2015 ◽  
Vol 2015 ◽  
pp. 1-8
Author(s):  
Yunlong Lu ◽  
Weiwei Yang ◽  
Wenyu Li ◽  
Xiaowei Jiang ◽  
Yueting Yang

A new trust region method is presented, which combines nonmonotone line search technique, a self-adaptive update rule for the trust region radius, and the weighting technique for the ratio between the actual reduction and the predicted reduction. Under reasonable assumptions, the global convergence of the method is established for unconstrained nonconvex optimization. Numerical results show that the new method is efficient and robust for solving unconstrained optimization problems.


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