scholarly journals Decrease of the Penalty Parameter in Differentiable Penalty Function Methods

2011 ◽  
Vol 01 (01) ◽  
pp. 8-14 ◽  
Author(s):  
Roohollah Aliakbari Shandiz ◽  
Emran Tohidi



2015 ◽  
Vol 32 (01) ◽  
pp. 1540006 ◽  
Author(s):  
Zhongwen Chen ◽  
Shicai Miao

In this paper, we propose a class of new penalty-free method, which does not use any penalty function or a filter, to solve nonlinear semidefinite programming (NSDP). So the choice of the penalty parameter and the storage of filter set are avoided. The new method adopts trust region framework to compute a trial step. The trial step is then either accepted or rejected based on the some acceptable criteria which depends on reductions attained in the nonlinear objective function and in the measure of constraint infeasibility. Under the suitable assumptions, we prove that the algorithm is well defined and globally convergent. Finally, the preliminary numerical results are reported.



2018 ◽  
pp. 315-336
Author(s):  
Melvyn W. Jeter


1976 ◽  
Vol 23 (1) ◽  
pp. 50-58 ◽  
Author(s):  
Richard P. O'Neill ◽  
William B. Widhelm


1990 ◽  
Vol 27 (1) ◽  
pp. 371-380 ◽  
Author(s):  
Anthony V. Fiacco




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