59 citations to https://www.mathnet.ru/rus/at6095
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D. E. Kvasov, M. S. Mukhametzhanov, “Metaheuristic vs. Deterministic global optimization algorithms: the univariate case”, Appl. Math. Comput., 318 (2018), 245–259
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V. Grishagin, R. Israfilov, Ya. Sergeyev, “Convergence conditions and numerical comparison of global optimization methods based on dimensionality reduction schemes”, Appl. Math. Comput., 318 (2018), 270–280
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Zh. Jin, D. Y. Gao, “On modeling and global solutions for d.c. optimization problems by canonical duality theory”, Appl. Math. Comput., 296 (2017), 168–181
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J. W. Gillard, D. E. Kvasov, “Lipschitz optimization methods for fitting a sum of damped sinusoids to a series of observations”, Stat. Interface, 10:1 (2017), 59–70
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Ya. D. Sergeyev, D. E. Kvasov, M. S. Mukhametzhanov, “Operational zones for comparing metaheuristic and deterministic one-dimensional global optimization algorithms”, Math. Comput. Simul., 141:SI (2017), 96–109
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Ya. D. Sergeyev, M. S. Mukhametzhanov, D. E. Kvasov, D. Lera, “Derivative-free local tuning and local improvement techniques embedded in the univariate global optimization”, J. Optim. Theory Appl., 171:1 (2016), 186–208
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E. Baeyens, A. Herreros, J. R. Peran, “A direct search algorithm for global optimization”, Algorithms, 9:2 (2016), 40
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Ya. D. Sergeyev, D. E. Kvasov, M. S. Mukhametzhanov, “On the least-squares fitting of data by sinusoids”, Advances in Stochastic and Deterministic Global Optimization, Springer Optimization and Its Applications, 107, eds. P. Pardalos, A. Zhigljavsky, J. Zilinskas, Springler, 2016, 209–226
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D. Lera, Ya. Sergeyev, “Remarks on global optimization using space-filling curves”, Numerical computations: theory and algorithms (NUMTA-2016), AIP Conf. Proc., 1776, eds. Y. Sergeyev, D. Kvasov, F. DellAccio, M. Mukhametzhanov, Amer. Inst. Phys., 2016, UNSP 060010
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V. Ya. Modorskii, D. F. Gaynutdinova, V. P. Gergel, K. A. Barkalov, AIP Conference Proceedings, 1738, 2016, 400013