Публикации

По первому этапу проекта

  1. Andrey Pepelyshev and Anatoly Zhigljavsky. SSA analysis and forecasting of records for Earth temperature and ice extents. Statistics and Its Interface. 10, No.1, pp. 151-163, 2017.
    DOI: 10.4310/SII.2017.v10.n1.a14
    Accession Number WoS: 000386413100015
    Scopus EID: 2-s2.0-85008219560
  2. Andrey Pepelyshev, Yuri Staroselskiy, and Anatoly Zhigljavsky. Adaptive targeting for online Advertisement. LNCS 9432, pp. 240–251, 2015.
    DOI: 10.1007/978-3-319-27926-8_21
    Scopus EID: 2-s2.0-84955269375
  3. Daniela Lera, Yaroslav D. Sergeyev. Space-filling curves and multiple estimates of Hölder constants in derivative-free global optimization. AIP Conference Proceedings, 1738, 400008, 2016.
    DOI: 10.1063/1.4952196
    Accession Number WoS: 000380803300419
    Scopus EID: 2-s2.0-84984555025
  4. Dmitri E. Kvasov, Marat S. Mukhametzhanov. One-Dimensional Global Search: Nature-Inspired vs. Lipschitz Methods. AIP Conference Proceedings, 1738, 400012, 2016.
    DOI: 10.1063/1.4952200
    Accession Number WoS: 000380803300423
    Scopus EID: 2-s2.0-84984559431
  5. Jonathan Gillard, Anatoly Zhigljavsky. Global optimization for structured low rank approximation. AIP Conference Proceedings,  1738, 400003, 2016.
    DOI: 10.1063/1.4952191
    Accession Number WoS: 000380803300414
    Scopus EID: 2-s2.0-84984549652
  6. Konstantin Barkalov, Victor Gergel, Ilya Lebedev. Solving Global Optimization Problems on GPU Cluster. AIP Conference Proceedings, 1738, 400006, 2016.
    DOI: 10.1063/1.4952194
    Accession Number WoS: 000380803300417
    Scopus EID: 2-s2.0-84984559157
  7. Mauro Brunato and Roberto Battiti. Stochastic Local Search for Direct Training of Threshold Networks. Proc. 2015 International Joint Conference on Neural Networks, IEEE Publisher, pp. 1-8, 2015. 
    DOI: 10.1109/IJCNN.2015.7280770
    Scopus EID: 2-s2.0-84950996840
  8. Modorskii V.Ya., Gaynutdinova D.F., Gergel V.P., Barkalov K.A. Optimization in Design of Scientific Products for Purposes of Cavitation Problems. AIP Conference Proceedings, 1738, 400013, 2016.
    DOI: 10.1063/1.4952201
    Accession Number WoS: 000380803300424
    Scopus EID: 2-s2.0-84984549606
  9. Victor Gergel, Vladimir Grishagin, Alexander Gergel. Adaptive nested optimization scheme for multidimensional global search. Journal of Global Optimization, Vol. 66, No.1, pp. 35–51, 2016. 
    DOI: 10.1007/s10898-015-0355-7
    Accession Number WoS:
    Scopus EID:
  10. Vladimir A. Grishagin, Ruslan A. Israfilov. Global Search Acceleration in the Nested Optimization Scheme. AIP Conference Proceedings, 1738, 400010, 2016.
    DOI: 10.1063/1.4952198
    Accession Number WoS: 000380803300421
    Scopus EID: 2-s2.0-84984539098
  11. Vladimir Grishagin and Ruslan Israfilov. Multidimensional Constrained Global Optimization in Domains with Computable Boundaries. CEUR Workshop Proceedings, 1513, pp. 75-84, 2015.
    Scopus EID: 2-s2.0-84960949984
  12. Yaroslav D. Sergeyev, Dmitri E. Kvasov, Marat S. Mukhametzhanov. Comments upon the Usage of Derivatives in Lipschitz Global Optimization. AIP Conference Proceedings,  1738, 400004, 2016.
    DOI:  10.1063/1.4952192
    Accession Number WoS: 000380803300415
    Scopus EID: 2-s2.0-84984545986
  13. 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. Journal of Optimization Theory and Applications, Vol. 171, 1, pp 186–208, 2016.
    DOI: 10.1007/s10957-016-0947-5
    Accession Number WoS: 000383577500009
    Scopus EID: 2-s2.0-84968593869

По второму этапу проекта

  1. Afraimovich L.G., Katerov A.S., Prilutskii M.Kh. Multi-Index Traffic Problems with 1-Nested Structure. Automation and Remote Control, 77, No. 11, pp. 1894–1913, 2016.
    DOI: 10.1134/S0005117916110023
    Scopus EID: 2-s2.0-8499473060
  2. Barkalov K.A., Gergel V.P. Parallel global optimization on GPU. Journal of Global Optimization, 66, No. 1, pp. 3–20, 2016.
    DOI: 10.1007/s10898-016-0411-y
    Accession Number WoS: 000382141100002
    Scopus EID: 2-s2.0-84957945752
  3. Barkalov K., Lebedev I. Local tuning in multilevel scheme of parallel global optimization. AIP Conference Proceedings, Vol. 1776, pp. 060006-1 – 060006-4, 2016.
    DOI: 10.1063/1.4965340
    Scopus EID: 2-s2.0-84995460849
  4. Barkalov K.A., Lebedev I.G. Solving Multidimensional Global Optimization Problems Using Graphics Accelerators. Communications in Computer and Information Science, 
    DOI: 10.1007/978-3-319-55669-7_18
  5. Баркалов К.А., Лебедев И.Г. Решение задач глобальной оптимизации на графических ускорителях. Суперкомпьютерные дни в России: Труды международной конференции (26-27 сентября 2016 г., г. Москва), с. 640-650, 2016.
  6. Barkalov K.A., Sysoyev A.V., Lebedev I.G., Sovrasov V.V. Solving GENOPT Problems with the Use of ExaMin Solver. Lecture Notes in Computer Science, Vol. 10079, pp. 283-295, 2016.
    DOI: 10.1007/978-3-319-50349-3_24
  7. Battiti R., Sergeyev Ya.D., Brunato M., Kvasov D.E. GENOPT 2016: Design of a generalization-based challenge in global optimization. AIP Conference Proceedings, Vol. 1776, pp. 060005-1 – 060005-4, 2016.
    DOI: 10.1063/1.4965339
    Scopus EID: 2-s2.0-84995494155
  8. Brunato M., Battiti R. A Telescopic Binary Learning Machine for Training Neural Networks. IEEE Transactions on Neural Networks and Learning Systems, Vol. PP, No.99, pp. 1-13, 2016.
    DOI: 10.1109/TNNLS.2016.2537300
    Scopus EID: 2-s2.0-84961825602
  9. Gillard J.W., Kvasov D. E. Lipschitz optimization methods for fitting a sum of damped sinusoids to a series of observations. Statistics and Its Interface, Volume 10, No. 1, pp. 59–70, 2017.
    DOI: 10.4310/SII.2017.v10.n1.a6
    Accession Number WoS: 000386413100007
  10. Gillard J., Kvasov D., Zhigljavsky A. Optimization Problems in Structured Low Rank Approximation. AIP Conference Proceedings, Vol. 1776, pp. 060004-1 – 060004-4, 2016.
    DOI: 10.1063/1.4965338
    Scopus EID: 2-s2.0-84995449819
  11. Grishagin V.A., Israfilov R.A., Sergeyev Ya.D. Comparative Efficiency of Dimensionality Reduction Schemes in Global Optimization. AIP Conference Proceedings, Vol. 1776, pp. 060011-1 – 060011-4, 2016.
    DOI: 10.1063/1.4965345
    Scopus EID: 2-s2.0-84995520651
  12. Zhigljavsky A., Golyandina N., Gryaznov S. Deconvolution of a discrete uniform distribution. Statistics and Probability Letters, Vol. 118, pp. 37-44, 2016.
    DOI: 10.1016/j.spl.2016.06.006
    Accession Number WoS: 000381839500006
    Scopus EID: 2-s2.0-84976908752
  13. Žilinskas A., Zhigljavsky A. Stochastic Global Optimization: A Review on the Occasion of 25 Years of Informatica. Informatica, Vol. 27, No. 2, pp. 229–256, 2016.
    DOI: 10.15388/Informatica.2016.83
    Accession Number WoS: 000379100600001
    Scopus EID: 2-s2.0-84987948207
  14. Cococcioni M., Pappalardo M., Sergeyev Ya.D. Towards lexicographic multi-objective linear programming using grossone methodology. AIP Conference Proceedings, Vol. 1776, pp. 090040-1 – 090040-5, 2016.
    DOI: 10.1063/1.4965404
    Scopus EID: 2-s2.0-84995520586
  15. Lera D., Sergeyev Ya.D. Remarks on Global Optimization Using Space-Filling Curves. AIP Conference Proceedings, Vol. 1776, pp. 060010-1 – 060010-4, 2016.
    DOI: 10.1063/1.4965344
    Scopus EID: 2-s2.0-84995467847
  16. Mazzia F., Sergeyev Ya.D., Iavernaro F., Amodio P., Mukhametzhanov M.S. Numerical methods for solving ODEs on the infinity computer. AIP Conference Proceedings, Vol. 1776, pp. 090033-1 – 090033-4, 2016.
    DOI: 10.1063/1.4965397
    Scopus EID: 2-s2.0-84995475415
  17. Sergeyev Ya.D. The exact (up to infinitesimals) infinite perimeter of the Koch snowflake and its finite area. Communications in Nonlinear Science and Numerical Simulation, Vol. 31, pp. 21-29, 2016.
    DOI: 10.1016/j.cnsns.2015.07.004
    Accession Number WoS: 0003620468000037
    Scopus EID: 2-s2.0-84940476954
  18. Sergeyev Ya.D., Kvasov D.E. Deterministic Global Optimization. An Introduction to the Diagonal Approach. Springer, 2017.
  19. Sergeyev Ya.D., Kvasov D.E., Mukhametzhanov M.S. On the Least-Squares Fitting of Data by Sinusoids. Advances in Stochastic and Deterministic Global Optimization, Series Springer Optimization and Its Applications, Springer International Publishing, Vol.107, pp. 209-226, 2016.
    DOI: 10.1007/978-3-319-29975-4_11
    Scopus EID: 2-s2.0-84994479867
  20. Sergeyev Ya.D., Kvasov D.E., Mukhametzhanov M.S., De Franco A. Acceleration Techniques in the Univariate Lipschitz Global Optimization. AIP Conference Proceedings, Vol.1776, pp. 090051-1 – 090051-4, 2016.
    DOI: 10.1063/1.4965415
    Scopus EID: 2-s2.0-84995475808
  21. Sergeyev Ya.D., Mukhametzhanov M.S., Mazzia F., Iavernaro F., Amodio P. Numerical Methods for Solving Initial Value Problems on the Infinity Computer. International Journal of Unconventional Computing, Vol. 12, No. 1, pp. 3–23, 2016.
    Accession Number WoS: 000376156600002
    Scopus EID: 2-s2.0-84969277810

По третьему этапу проекта

Монографии

  1. Golyandina N., Korobeynikov A., Zhigljavsky A. Singular Spectrum Analysis with R. Springer, Heidelberg. 296 p. (принята к публикации)
  2. Battiti R., Kvasov D., Sergeyev Y. (eds). Learning and Intelligent Optimization.11th International Conference, LION 11, Nizhny Novgorod, Russia, June 19-21, 2017, Revised Selected Papers. Lecture Notes in Computer Science, vol 10556. Springer, Cham . 403 pp. (XIII + 390)
    DOI: 10.1007/978-3-319-69404-7

Статьи

  1. Vladimir Grishagin, Ruslan Israfilov, Yaroslav Sergeyev. Convergence conditions and numerical comparison of global optimization methods based on dimensionality reduction schemes. Applied Mathematics and Computation (2018) vol. 318, pp.  270–280
    DOI: 10.1016/j.amc.2017.06.036
    Scopus EID: 2-s2.0-85025428828
    Accession Number WoS:  000415905500019
  2. 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 (2017) vol. 141, pp.  96–109.
    DOI: 10.1016/j.matcom.2016.05.006
    Accession Number WoS: 000408783100009
    Scopus EID: 2-s2.0-84977633110
  3. Dmitri E. Kvasov, Marat S. Mukhametzhanov. Metaheuristic vs. deterministic global optimization algorithms: The univariate case. Applied Mathematics and Computation 318 (2018) 245–259.
    DOI:10.1016/j.amc.2017.05.014
    Accession Number WoS: 000415905500017
    Scopus EID: 2-s2.0-85019578331
  4. Marco Cococcioni, Massimo Pappalardo , Yaroslav D. Sergeyev. Lexicographic multi-objective linear programming using grossone methodology: Theory and algorithm. Applied Mathematics and Computation 318 (2018) 298–311.
    DOI:10.1016/j.amc.2017.05.058
    Accession Number WoS: 000415905500022
    Scopus EID: 2-s2.0-85020121970
  5. Jonathan Gillard, Anatoly Zhigljavsky. Optimal estimation of direction in regression models with large number of parameters. Applied Mathematics and Computation 318 (2018) 281–289.
    DOI:10.1016/j.amc.2017.05.050
    Accession Number WoS: 000415905500020
    Scopus EID: 2-s2.0-85020019797
  6. Gillard J., Zhigljavsky A. (2017) Global Optimization Challenges in Structured Low Rank Approximation. In: Battiti R., Kvasov D., Sergeyev Y. (eds) Learning and Intelligent Optimization. LION 2017. Lecture Notes in Computer Science, vol 10556. Pp. 326–330. Springer, Cham
    DOI:10.1007/978-3-319-69404-7_26
    Scopus: 2-s2.0-85034236220
  7. Pepelyshev A., Kornikov V., Zhigljavsky A. (2017) Statistical Estimation in Global Random Search Algorithms in Case of Large Dimensions. In: Battiti R., Kvasov D., Sergeyev Y. (eds) Learning and Intelligent Optimization. LION 2017. Lecture Notes in Computer Science, vol 10556. Pp. 364-369. Springer, Cham
    DOI:10.1007/978-3-319-69404-7_32
    Scopus EID: 2-s2.0-85034237755
  8. Renato De Leone, Giovanni Fasano,·Yaroslav D. Sergeyev. Planar methods and grossone for the Conjugate Gradient breakdown in nonlinear programming. Computational Optimization and Applications (2017)
    DOI 10.1007/s10589-017-9957-y
    Scopus EID: 2-s2.0-85031939975
  9. Manlio Gaudioso, Giovanni Giallombardo, Marat Mukhametzhanov. Numerical infinitesimals in a variable metric method for convex nonsmooth optimization. Applied Mathematics and Computation 318 (2018) 312–320
    DOI: 10.1016/j.amc.2017.07.057
    Accession Number WoS: 000415905500023
    Scopus EID: 2-s2.0-85026870535
  10. Sergeyev Y.D., Kvasov D.E., Mukhametzhanov M.S. (2017) Emmental-Type GKLS-Based Multiextremal Smooth Test Problems with Non-linear Constraints. In: Battiti R., Kvasov D., Sergeyev Y. (eds) Learning and Intelligent Optimization. LION 2017. Lecture Notes in Computer Science, vol 10556, pp. 383–388. Springer, Cham
    DOI:10.1007/978-3-319-69404-7_35
    Scopus EID: 2-s2.0-85034254302
  11. Pepelyshev, A., Zhigljavsky, A.,Žilinskas, A. Performance of global random search algorithms for large dimensions. J Glob Optim (2017) pp.1-15.
    DOI: 10.1007/s10898-017-0535-8
    Scopus EID: 2-s2.0-85020083322
  12. Daniela Lera, Yaroslav D. Sergeyev. GOSH: derivative-free global optimization using multi-dimensional space-filling curves. Journal of Global Optimization (2017).
    DOI: 10.1007/s10898-017-0589-7
  13. Yaroslav D. Sergeyev, Dmitri E. Kvasov, Marat S. Mukhametzhanov. On strong homogeneity of a class of global optimization algorithms working with infinite and infinitesimal scales. Communications in Nonlinear Science and Numerical Simulation, vol. 59 (2018) pp. 319-330.
    DOI: 10.1016/j.cnsns.2017.11.013
  14. Tahir Emre Kalaici, Roberto Battiti. A reactive self-tuning scheme for multilevel graph partitioning. Applied Mathematics and Computation, vol. 318, pp. 227-244. 2018.
    DOI: 10.1016/j.amc.2017.08.031
    Accession Number WoS: 000415905500016
    Scopus EID:  2-s2.0-85029290402
  15. Афраймович Л.Г. Нижняя оценка для трехиндексной аксиальной задачи о назначениях с 1,2-декомпозиционной матрицей стоимостей. Вестник Волжской государственной академии водного транспорта. Выпуск 49, с. 25-29. 2017
  16. Гришагин В.А., Исрафилов Р.А. Параллельная реализация адаптивной многошаговой схемы редукции размерности для задач глобальной оптимизации. Суперкомпьютерные дни в России: Труды международной конференции (25-26 сентября 2017 г., г. Москва). С. 671-682. 2017
  17. Баркалов К.А., Гетманская А.А., Исрафилов Р.А. Применение адаптивной схемы редукции размерности для задач многоэкстремальной оптимизации с нелинейными ограничениями. Вестник ВГАВТ, 2018 (принята к печати)