On the Least-Squares Fitting of Data by Sinusoids. - Yaroslav D. Sergeyev; Dmitri E. Kvasov; Marat S. Mukhametzhanov (Advances in Stochastic and Deterministic Global Optimization, 2016)

Numerical Methods for Solving Initial Value Problems on the Infinity Computer. - Yaroslav D. Sergeyev; Marat S. Mukhametzhanov; Francesca Mazzia; Felice Iavernaro; Pierluigi Amodio (Int. J. Unconv. Comput., 2016)

Derivative-Free Local Tuning and Local Improvement Techniques Embedded in the Univariate Global Optimization. - Yaroslav D. Sergeyev; Marat S. Mukhametzhanov; Dmitri E. Kvasov; Daniela Lera (J. Optim. Theory Appl., 2016)

Emmental-Type GKLS-Based Multiextremal Smooth Test Problems with Non-linear Constraints. - Yaroslav D. Sergeyev; Dmitri E. Kvasov; Marat S. Mukhametzhanov (LION, 2017)

A generalized Taylor method of order three for the solution of initial value problems in standard and infinity floating-point arithmetic. - Pierluigi Amodio; Felice Iavernaro; Francesca Mazzia; Marat S. Mukhametzhanov; Yaroslav D. Sergeyev (Math. Comput. Simul., 2017)

Operational zones for comparing metaheuristic and deterministic one-dimensional global optimization algorithms. - Yaroslav D. Sergeyev; Dmitri E. Kvasov; Marat S. Mukhametzhanov (Math. Comput. Simul., 2017)

Numerical infinitesimals in a variable metric method for convex nonsmooth optimization. - Manlio Gaudioso; Giovanni Giallombardo; Marat S. Mukhametzhanov (Appl. Math. Comput., 2018)

Metaheuristic vs. deterministic global optimization algorithms: The univariate case. - Dmitri E. Kvasov; Marat S. Mukhametzhanov (Appl. Math. Comput., 2018)

On strong homogeneity of a class of global optimization algorithms working with infinite and infinitesimal scales. - Yaroslav D. Sergeyev; Dmitri E. Kvasov; Marat S. Mukhametzhanov (Commun. Nonlinear Sci. Numer. Simul., 2018)

A Simulink-Based Infinity Computer Simulator and Some Applications. - Alberto Falcone; Alfredo Garro; Marat S. Mukhametzhanov; Yaroslav D. Sergeyev (NUMTA (2), 2019)

On Acceleration of Derivative-Free Univariate Lipschitz Global Optimization Methods. - Dmitri E. Kvasov; Marat S. Mukhametzhanov; Maria Chiara Nasso; Yaroslav D. Sergeyev (NUMTA (2), 2019)

Representation of grossone-based arithmetic in simulink for scientific computing. - Alberto Falcone; Alfredo Garro; Marat S. Mukhametzhanov; Yaroslav D. Sergeyev (Soft Comput., 2020)

A Simulink-based software solution using the Infinity Computer methodology for higher order differentiation. - Alberto Falcone; Alfredo Garro; Marat S. Mukhametzhanov; Yaroslav D. Sergeyev (Appl. Math. Comput., 2021)

Computation of higher order Lie derivatives on the Infinity Computer. - Felice Iavernaro; Francesca Mazzia; Marat S. Mukhametzhanov; Yaroslav D. Sergeyev (J. Comput. Appl. Math., 2021)

Novel local tuning techniques for speeding up one-dimensional algorithms in expensive global optimization using Lipschitz derivatives. - Yaroslav D. Sergeyev; Maria Chiara Nasso; Marat S. Mukhametzhanov; Dmitri E. Kvasov (J. Comput. Appl. Math., 2021)

On the search of the shape parameter in radial basis functions using univariate global optimization methods. - Roberto Cavoretto; Alessandra De Rossi; Marat S. Mukhametzhanov; Yaroslav D. Sergeyev (J. Glob. Optim., 2021)

Simulation of hybrid systems under Zeno behavior using numerical infinitesimals. - Alberto Falcone; Alfredo Garro; Marat S. Mukhametzhanov; Yaroslav D. Sergeyev (Commun. Nonlinear Sci. Numer. Simul., 2022)

High Precision Differentiation Techniques for Data-Driven Solution of Nonlinear PDEs by Physics-Informed Neural Networks. - Marat S. Mukhametzhanov (CoRR, 2022)

A Generator of Multiextremal Test Classes With Known Solutions for Black-Box-Constrained Global Optimization. - Yaroslav D. Sergeyev; Dmitri E. Kvasov; Marat S. Mukhametzhanov (IEEE Trans. Evol. Comput., 2022)

Advantages of the usage of the Infinity Computer for reducing the Zeno behavior in hybrid system models. - Alberto Falcone; Alfredo Garro; Marat S. Mukhametzhanov; Yaroslav D. Sergeyev (Soft Comput., 2023)