Objective-derivative-free methods for constrained optimization

2002 ◽  
Vol 92 (1) ◽  
pp. 37-59 ◽  
Author(s):  
S. Lucidi ◽  
M. Sciandrone ◽  
P. Tseng
Author(s):  
Sunil Kumar ◽  
Deepak Kumar ◽  
Janak Raj Sharma ◽  
Ioannis K. Argyros

Abstract Many optimal order multiple root techniques, which use derivatives in the algorithm, have been proposed in literature. Many researchers tried to construct an optimal family of derivative-free methods for multiple roots, but they did not get success in this direction. With this as a motivation factor, here, we present a new optimal class of derivative-free methods for obtaining multiple roots of nonlinear functions. This procedure involves Traub–Steffensen iteration in the first step and Traub–Steffensen-like iteration in the second step. Efficacy is checked on a good number of relevant numerical problems that verifies the efficient convergent nature of the new methods. Moreover, we find that the new derivative-free methods are just as competent as the other existing robust methods that use derivatives.


2020 ◽  
Vol 76 (4) ◽  
pp. 841-861
Author(s):  
Min Xi ◽  
Wenyu Sun ◽  
Yannan Chen ◽  
Hailin Sun

2018 ◽  
Vol 71 (2) ◽  
pp. 307-329 ◽  
Author(s):  
Charles Audet ◽  
Andrew R. Conn ◽  
Sébastien Le Digabel ◽  
Mathilde Peyrega

2014 ◽  
Vol 114 ◽  
pp. 22-37 ◽  
Author(s):  
Masoud Asadollahi ◽  
Geir Nævdal ◽  
Mohsen Dadashpour ◽  
Jon Kleppe

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