9 citations to 10.1023/A:1014063303984 (Crossref Cited-By Service)

1. Yaroslav D. Sergeyev, Antonio Candelieri, Dmitri E. Kvasov, Riccardo Perego, “Safe global optimization of expensive noisy black-box functions in the $\delta $-Lipschitz framework”, Soft Comput, 24, no. 23, 2020, 17715  
2. A. Galántai, J. Abaffy, “Always convergent iteration methods for nonlinear equations of Lipschitz functions”, Numer Algor, 69, no. 2, 2015, 443  
3. Oleg Valerievich Khamisov, “Нахождение корней нелинейного уравнения методом вогнутых опорных функций”, Математические заметки, 98, no. 3, 2015, 427  
4. Dmitri E. Kvasov, Yaroslav D. Sergeyev, “Univariate geometric Lipschitz global optimization algorithms”, Numerical Algebra, Control & Optimization, 2, no. 1, 2012, 69  
5. Yaroslav D. Sergeyev, Marat S. Mukhametzhanov, Dmitri E. Kvasov, Daniela Lera, “Derivative-Free Local Tuning and Local Improvement Techniques Embedded in the Univariate Global Optimization”, J Optim Theory Appl, 171, no. 1, 2016, 186  
6. O. V. Khamisov, “Finding roots of nonlinear equations using the method of concave support functions”, Math Notes, 98, no. 3-4, 2015, 484  
7. A. Galántai, “Always convergent methods for nonlinear equations of several variables”, Numer Algor, 78, no. 2, 2018, 625  
8. Daniela Lera, Yaroslav D. Sergeyev, “Acceleration of Univariate Global Optimization Algorithms Working with Lipschitz Functions and Lipschitz First Derivatives”, SIAM J. Optim., 23, no. 1, 2013, 508  
9. Yaroslav D. Sergeyev, Dmitri E. Kvasov, Marat S. Mukhametzhanov, “Operational zones for comparing metaheuristic and deterministic one-dimensional global optimization algorithms”, Mathematics and Computers in Simulation, 141, 2017, 96