Stochastic Global Optimization: A Review on the Occasion of 25 Years of Informatica

Žilinskas, Antanas

doi:10.15388/Informatica.2016.83

AIP Conference Proceedings

Antanas Žilinskas

https://doi.org/10.1063/1.5089987

Conference: AIP Conference Proceedings Volume 2070 (2019), p. 020020

A Partition Based Bayesian Multi-objective Optimization Algorithm

Antanas Žilinskas, Linas Litvinas

https://doi.org/10.1007/978-3-030-40616-5_50

Book: Lecture Notes in Computer Science (Numerical Computations: Theory and Algorithms) Volume 11974 (2020), p. 511

Safe Global Optimization

Antonio Candelieri, Dmitri E. Kvasov, Yaroslav D. Sergeyev

https://doi.org/10.1007/978-3-030-54621-2_765-1

Book: (2023), p. 1

Learning Enabled Constrained Black-Box Optimization

F. Archetti, A. Candelieri, B. G. Galuzzi, R. Perego

https://doi.org/10.1007/978-3-030-66515-9_1

Book: Springer Optimization and Its Applications (Black Box Optimization, Machine Learning, and No-Free Lunch Theorems) Volume 170 (2021), p. 1

Bayesian Optimization Based on Simulation Conditionally to Subvariety

Frédéric Dambreville

https://doi.org/10.1007/978-3-030-92666-3_11

Book: Lecture Notes in Networks and Systems (Modelling, Computation and Optimization in Information Systems and Management Sciences) Volume 363 (2022), p. 120

Simulation Conditionally to a Subvariety and Application to Bayesian Optimization: A Dichotomous Approach

Frédéric Dambreville

https://doi.org/10.1007/978-3-031-23149-0_10

Book: Lecture Notes in Networks and Systems (Simulation and Modeling Methodologies, Technologies and Applications) Volume 601 (2023), p. 178

From Global Optimization to Optimal Learning

Francesco Archetti, Antonio Candelieri

https://doi.org/10.1007/978-3-030-24494-1_2

Book: SpringerBriefs in Optimization (Bayesian Optimization and Data Science) (2019), p. 19

AIP Conference Proceedings

Antanas Žilinskas

https://doi.org/10.1063/1.4965307

Conference: AIP Conference Proceedings Volume 1776 (2016), p. 020001

INTERNATIONAL CONFERENCE OF NUMERICAL ANALYSIS AND APPLIED MATHEMATICS ICNAAM 2021

Dmitri E. Kvasov, Daniela Lera, Yaroslav D. Sergeyev

https://doi.org/10.1063/5.0162069

Conference: INTERNATIONAL CONFERENCE OF NUMERICAL ANALYSIS AND APPLIED MATHEMATICS ICNAAM 2021 (INTERNATIONAL CONFERENCE OF NUMERICAL ANALYSIS AND APPLIED MATHEMATICS ICNAAM 2021) Volume 2849 (2023), p. 450033

Lipschitz Expensive Global Optimization

Dmitri E. Kvasov, Yaroslav D. Sergeyev

https://doi.org/10.1007/978-3-030-54621-2_764-1

Book: (2023), p. 1

AIP Conference Proceedings

Antanas Žilinskas, Anatoly Zhigljavsky, Vladimir Nekrutkin, Vladimir Kornikov

https://doi.org/10.1063/1.5090010

Conference: AIP Conference Proceedings Volume 2070 (2019), p. 020043

2D/3D Shaped Radiation Patterns of Sunflower and Conformal Antenna Arrays Using Phase Synthesis

Saber Helmy Zainud-Deen, Doaa Mohammed Zaki Azzam, Hend Abd El-Azem Malhat

https://doi.org/10.1007/s11277-020-07602-w

Journal: Wireless Personal Communications Volume 115, Issue 1 (2020), p. 877

A Bayesian optimization approach to find Nash equilibria

Victor Picheny, Mickael Binois, Abderrahmane Habbal

https://doi.org/10.1007/s10898-018-0688-0

Journal: Journal of Global Optimization Volume 73, Issue 1 (2019), p. 171

A hybrid of Bayesian approach based global search with clustering aided local refinement

Antanas Žilinskas, Gražina Gimbutienė

https://doi.org/10.1016/j.cnsns.2019.104857

Journal: Communications in Nonlinear Science and Numerical Simulation Volume 78 (2019), p. 104857

A hybrid of the simplicial partition-based Bayesian global search with the local descent

Antanas Žilinskas, Linas Litvinas

https://doi.org/10.1007/s00500-020-05095-0

Journal: Soft Computing Volume 24, Issue 23 (2020), p. 17601

Aggregated GP-based Optimization for Contaminant Source Localization

Tipaluck Krityakierne, Duangkamon Baowan

https://doi.org/10.1016/j.orp.2020.100151

Journal: Operations Research Perspectives Volume 7 (2020), p. 100151

An Improved Butterfly Optimization Algorithm for Engineering Design Problems Using the Cross-Entropy Method

Guocheng Li, Fei Shuang, Pan Zhao, Chengyi Le

https://doi.org/10.3390/sym11081049

Journal: Symmetry Volume 11, Issue 8 (2019), p. 1049

Applying “Two Heads Are Better Than One” Human Intelligence to Develop Self-Adaptive Algorithms for Ridesharing Recommendation Systems

Fu-Shiung Hsieh

https://doi.org/10.3390/electronics13122241

Journal: Electronics Volume 13, Issue 12 (2024), p. 2241

Bi-objective decision making in global optimization based on statistical models

Antanas Žilinskas, James Calvin

https://doi.org/10.1007/s10898-018-0622-5

Journal: Journal of Global Optimization Volume 74, Issue 4 (2019), p. 599

Computational Diagnostics of Jacobi Unstable Dynamical Systems with the Use of Hybrid Algorithms of Global Optimization

P.M. Shkapov, A.V. Sulimov, V.D. Sulimov

https://doi.org/10.18698/1812-3368-2021-4-40-56

Journal: Herald of the Bauman Moscow State Technical University. Series Natural Sciences Issue 4 (97) (2021), p. 40

Constrained optimization of black-box stochastic systems using a novel feasibility enhanced Kriging-based method

Zilong Wang, Marianthi Ierapetritou

https://doi.org/10.1016/j.compchemeng.2018.07.016

Journal: Computers & Chemical Engineering Volume 118 (2018), p. 210

Finding optimal points for expensive functions using adaptive RBF-based surrogate model via uncertainty quantification

Ray-Bing Chen, Yuan Wang, C. F. Jeff Wu

https://doi.org/10.1007/s10898-020-00916-w

Journal: Journal of Global Optimization Volume 77, Issue 4 (2020), p. 919

Globally-biased BIRECT algorithm with local accelerators for expensive global optimization

Remigijus Paulavičius, Yaroslav D. Sergeyev, Dmitri E. Kvasov, Julius Žilinskas

https://doi.org/10.1016/j.eswa.2019.113052

Journal: Expert Systems with Applications Volume 144 (2020), p. 113052

Monitoring the Area Change in the Three Gorges Reservoir Riparian Zone Based on Genetic Algorithm Optimized Machine Learning Algorithms and Sentinel-1 Data

Baisheng Xu, Wei Wu, Haohui Ye, Xinrong Li, Hongbin Liu

https://doi.org/10.3390/rs15235456

Journal: Remote Sensing Volume 15, Issue 23 (2023), p. 5456

Non-Stationary Stochastic Global Optimization Algorithms

Jonatan Gomez, Andres Rivera

https://doi.org/10.3390/a15100362

Journal: Algorithms Volume 15, Issue 10 (2022), p. 362

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

https://doi.org/10.1016/j.cam.2020.113134

Journal: Journal of Computational and Applied Mathematics Volume 383 (2021), p. 113134

On convergence rate of a rectangular partition based global optimization algorithm

James Calvin, Gražina Gimbutienė, William O. Phillips, Antanas Žilinskas

https://doi.org/10.1007/s10898-018-0636-z

Journal: Journal of Global Optimization Volume 71, Issue 1 (2018), p. 165

On the convergence rate of the quasi – Monte Carlo method of search for extremum

A S Tikhomirov

https://doi.org/10.1088/1742-6596/1352/1/012051

Journal: Journal of Physics: Conference Series Volume 1352, Issue 1 (2019), p. 012051

On the program implementation of a Markov homogeneous monotonous random search algorithm of an extremum

A S Tikhomirov

https://doi.org/10.1088/1757-899X/441/1/012055

Journal: IOP Conference Series: Materials Science and Engineering Volume 441 (2018), p. 012055

On the program implementation of a Markov homogeneous random search algorithm of an extremum with Ingber’s distribution

A S Tikhomirov, N Yu Kropacheva

https://doi.org/10.1088/1742-6596/1352/1/012055

Journal: Journal of Physics: Conference Series Volume 1352, Issue 1 (2019), p. 012055

On the program implementation of a Markov homogeneous random search algorithm of an extremum with normal distributions

A S Tikhomirov

https://doi.org/10.1088/1742-6596/1352/1/012052

Journal: Journal of Physics: Conference Series Volume 1352, Issue 1 (2019), p. 012052

On the program implementation of a Markov inhomogeneous random search algorithm with normal distributions

A S Tikhomirov

https://doi.org/10.1088/1742-6596/1352/1/012053

Journal: Journal of Physics: Conference Series Volume 1352, Issue 1 (2019), p. 012053

On the program implementation of a simple Markov homogeneous random search algorithm of an extremum

A S Tikhomirov

https://doi.org/10.1088/1742-6596/1658/1/012058

Journal: Journal of Physics: Conference Series Volume 1658, Issue 1 (2020), p. 012058

On the program implementation of a simple Markov homogeneous random search algorithm of an extremum with Cauchy distributions

A S Tikhomirov

https://doi.org/10.1088/1742-6596/1658/1/012059

Journal: Journal of Physics: Conference Series Volume 1658, Issue 1 (2020), p. 012059

On the program implementation of a simple Markov homogeneous random search algorithm of an extremum with normal distributions

A S Tikhomirov

https://doi.org/10.1088/1742-6596/1658/1/012060

Journal: Journal of Physics: Conference Series Volume 1658, Issue 1 (2020), p. 012060

On the program implementation of a simple Markov homogeneous random search algorithm of an extremum with triangular distributions

A S Tikhomirov

https://doi.org/10.1088/1742-6596/1658/1/012061

Journal: Journal of Physics: Conference Series Volume 1658, Issue 1 (2020), p. 012061

On the search of the shape parameter in radial basis functions using univariate global optimization methods

R. Cavoretto, A. De Rossi, M. S. Mukhametzhanov, Ya. D. Sergeyev

https://doi.org/10.1007/s10898-019-00853-3

Journal: Journal of Global Optimization Volume 79, Issue 2 (2021), p. 305

Optimal Power Flow Using Particle Swarm Optimization of Renewable Hybrid Distributed Generation

Usama Khaled, Ali M. Eltamaly, Abderrahmane Beroual

https://doi.org/10.3390/en10071013

Journal: Energies Volume 10, Issue 7 (2017), p. 1013

Safe global optimization of expensive noisy black-box functions in the $$\delta $$-Lipschitz framework

Yaroslav D. Sergeyev, Antonio Candelieri, Dmitri E. Kvasov, Riccardo Perego

https://doi.org/10.1007/s00500-020-05030-3

Journal: Soft Computing Volume 24, Issue 23 (2020), p. 17715

Selection of a covariance function for a Gaussian random field aimed for modeling global optimization problems

Anatoly Zhigljavsky, Antanas Žilinskas

https://doi.org/10.1007/s11590-018-1372-5

Journal: Optimization Letters Volume 13, Issue 2 (2019), p. 249

Spark implementation of the enhanced Scatter Search metaheuristic: Methodology and assessment

Xoán C. Pardo, Pablo Argüeso-Alejandro, Patricia González, Julio R. Banga, Ramón Doallo

https://doi.org/10.1016/j.swevo.2020.100748

Journal: Swarm and Evolutionary Computation Volume 59 (2020), p. 100748

Surrogate-based feasibility analysis for black-box stochastic simulations with heteroscedastic noise

Zilong Wang, Marianthi Ierapetritou

https://doi.org/10.1007/s10898-018-0615-4

Journal: Journal of Global Optimization Volume 71, Issue 4 (2018), p. 957

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