Konstantin Barkalov, Ilya Lebedev, 10421, Parallel Computing Technologies, 2017, 396
Julien Marzat, Eric Walter, Hélène Piet-Lahanier, “A new expected-improvement algorithm for continuous minimax optimization”, J Glob Optim, 64, no. 4, 2016, 785
Remigijus Paulavičius, Julius Žilinskas, “Advantages of simplicial partitioning for Lipschitz optimization problems with linear constraints”, Optim Lett, 10, no. 2, 2016, 237
Dmitri E. Kvasov, Marat S. Mukhametzhanov, “Metaheuristic vs. deterministic global optimization algorithms: The univariate case”, Applied Mathematics and Computation, 318, 2018, 245
Magali Champion, Victor Picheny, Matthieu Vignes, “Inferring large graphs using $\ell _1$ ℓ 1 -penalized likelihood”, Stat Comput, 28, no. 4, 2018, 905
Fumina Mori, Masato Sugino, Kenta Kabashima, Takaaki Nara, Yasuhiko Jimbo, Kiyoshi Kotani, “Limiting parameter range for cortical-spherical mapping improves activated domain estimation for attention modulated auditory response”, Journal of Neuroscience Methods, 402, 2024, 110032
Xianghua Chu, Fulin Cai, Da Gao, Li Li, Jianshuang Cui, Su Xiu Xu, Quande Qin, “An artificial bee colony algorithm with adaptive heterogeneous competition for global optimization problems”, Applied Soft Computing, 93, 2020, 106391
Ilja Lebedev, Victor Gergel, “Heterogeneous Parallel Computations for Solving Global Optimization Problems1”, Procedia Computer Science, 66, 2015, 53
Yaroslav D. Sergeyev, Dmitri E. Kvasov, Marat S. Mukhametzhanov, “A Generator of Multiextremal Test Classes With Known Solutions for Black-Box-Constrained Global Optimization”, IEEE Trans. Evol. Computat., 26, no. 6, 2022, 1261
Haitao Liu, Shengli Xu, Xiaofang Wang, Junnan Wu, Yang Song, “A global optimization algorithm for simulation-based problems via the extended DIRECT scheme”, Engineering Optimization, 47, no. 11, 2015, 1441