Artículos de revistas
On The Differentiability Check In Gradient Sampling Methods
Registro en:
Optimization Methods And Software. Taylor & Francis Ltd, v. 31, p. 983 - 1007, 2016.
1055-6788
1029-4937
WOS:000382576500007
10.1080/10556788.2016.1178262
Autor
Helou
Elias Salomao; Santos
Sandra A.; Simoes
Lucas E. A.
Institución
Resumen
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) The present study aims to carefully discuss the importance of differentiability checks during the execution of methods based on gradient sampling. We stress the significance of this procedure not only from the theoretical perspective, but also in the practical implementation. We support our claims exhibiting illustrative examples where the absence of the differentiability check in the method prevents the achievement of the minimization problem solution. As possible alternatives, this manuscript presents two procedures that suppress the differentiability check without affecting the convergence of the method (both in theory and in practice). Lastly, by solving a difficult control problem, we show that besides the theoretical appeal our changes may also be useful to address real problems. 31 5 983 1007 CNPq [304032/2010-7, 311476/2014-7] FAPESP [2013/05475-7, 2013/07375-0, 2013/14615-7, 2013/16508-3] PRONEX Optimization Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)