An affine-scaling interior-point CBB method for box-constrained optimization

2007 ◽  
Vol 119 (1) ◽  
pp. 1-32 ◽  
Author(s):  
William W. Hager ◽  
Bernard A. Mair ◽  
Hongchao Zhang
2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Lingyun He ◽  
Peng Wang ◽  
Detong Zhu

An adaptive projected affine scaling algorithm of cubic regularization method using a filter technique for solving box constrained optimization without derivatives is put forward in the passage. The affine scaling interior-point cubic model is based on the quadratic probabilistic interpolation approach on the objective function. The new iterations are obtained by the solutions of the projected adaptive cubic regularization algorithm with filter technique. We prove the convergence of the proposed algorithm under some assumptions. Finally, experiments results showed that the presented algorithm is effective in detail.


2019 ◽  
Vol 07 (10) ◽  
pp. 2531-2536 ◽  
Author(s):  
Douglas Kwasi Boah ◽  
Stephen Boakye Twum

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