scholarly journals Penalty methods with stochastic approximation for stochastic nonlinear programming

2016 ◽  
Vol 86 (306) ◽  
pp. 1793-1820 ◽  
Author(s):  
Xiao Wang ◽  
Shiqian Ma ◽  
Ya-xiang Yuan
2019 ◽  
Vol 53 (1) ◽  
pp. 29-38
Author(s):  
Larbi Bachir Cherif ◽  
Bachir Merikhi

This paper presents a variant of logarithmic penalty methods for nonlinear convex programming. If the descent direction is obtained through a classical Newton-type method, the line search is done on a majorant function. Numerical tests show the efficiency of this approach versus classical line searches.


2008 ◽  
Vol 23 (2) ◽  
pp. 197-213 ◽  
Author(s):  
Richard H. Byrd ◽  
Jorge Nocedal ◽  
Richard A. Waltz

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