Pavlo Knopov: The scientific path and the formation of the Kyiv school of stochastic optimization
DOI:
https://doi.org/10.17721/1812-5409.2025/2.1Keywords:
stochastic optimization, control of stochastic systems, robust statistics, M-estimation, random fields, Kyiv school of probabilityAbstract
The article is dedicated to the 85th anniversary of Pavlo Solomonovych Knopov (b. May 21, 1940, Kyiv) – Doctor of Physical and Mathematical Sciences, Corresponding Member of the National Academy of Sciences of Ukraine; a leading specialist in stochastic optimization, statistics of random processes and fields, risk theory and control; author of over 250 scientific works and 13 monographs. Since 1999, he has headed the Department of Mathematical Methods of Operations Research at the V. M. Glushkov Institute of Cybernetics of the NAS of Ukraine, and since 1987 he has been a professor at Taras Shevchenko National University of Kyiv. He is a laureate of the State Prize of Ukraine in Science and Technology (2009), the V. M. Glushkov Prize (1997), the V. S. Mikhakevich (2021), and was awarded the title of Honored Scientist and Engineer of Ukraine (2021).
The Kyiv school of stochastic optimization, to the development of which P. S. Knopov made a significant contribution, represents a scientific phenomenon that combines probability theory, mathematical statistics, and control theory for solving decision-making problems under uncertainty. The article also outlines the difficult life and scientific path of the scholar, who went through the trials of his time and established himself as one of the leading mathematicians of his generation.
Pages of the article in the issue: 7 - 11
Language of the article: Ukrainian
References
1. Kasitskaya, E. J., & Knopov, P. S. (2002). Empirical Estimates in stochastic optimization and identification. Kluwer.
2. Chornei, R. K., Daduna, H., & Knopov, P. S. (2006). Control of Spatially Structured Random Processes and Random Fields with Applications. Springer.
3. Knopov, P. S., & Pardalos, P. M. (2009). Simulation and Optimization Methods in Risk and Reliability Theory. Nova Science Publishers, Inc.
4. Knopov, P. S., & Korkhin, A. S. (2013). Regression Analysis Under A Priory Parameter Restrictions. Springer.
5. Knopov, P. S., & Derieva, O. N. (2013). Estimation and Control problems for Stochastic Partial differential Equations. Springer.
6. Gaivoronskii, A., Knopov, P., & Zaslavskii, V. (2023). Modern Optimization Methods for Decision Making Under Risk and Uncertainty. CRC PRESS, Taylor Francis Group, Boca Raton, London, New York.
7. Gaivoronskii, A., Knopov, P., Norkin, V., & Zaslavski, V. (2025). Stochastic Modeling and Optimization Methods for Critical Infrastructure. Protection 1 Stochastic Modeling, ISTE-WILEY.
8. Gaivoronskii, A., Knopov, P., Norkin, V., & Zaslavski, V. (2025). Stochastic Modeling and Optimization Methods for Critical Infrastructure. Protection 2 Methods and Tools, ISTE-WILEY.
9. Knopov, P. S., & Kasitskaya, E. J. (1995). Properties of empirical estimates in stochastic optimization and identification problems. Annals of Operations Research, 56(1), 225–239
10. Knopov, P. S. (1997). On some classes of M-estimates for non-stationary regression models. Theory of Stochastic Processes, 3(19), 222–228.
11. Knopov, P. S. (1999). Markov fields and their applications in economic. Journal of Mathematical Sciences, 3923–3931.
12. Golodnikov, A. N., Knopov, P. S., Pardalos, P., & Uryasev, S. (2000). Optimization in the space of Distribution Functions and Applications in the Bayes Analysis. In Pardalos, P., Uryasev, S. (Eds.). Probabilistic Constrained Optimization: Methodology and Applications. Kluwer Academic Publishers, 102–131.
13. Knopov, P. S., Pardalos, P., & Yatsenko, V. A. (2001). Optimal Estimation of signal parameters using linear observation. Optimization and related topics. Kluwer Academic Publishers, 103–117.
14. Chornei, R., Daduna, H., & Knopov, P. (2004). Stochastic games for distributed players on graphs. Mathematical Methods of Operations Research, 60(2), 279–298
15. Chornei, R., Daduna, H., & Knopov, P. (2005). Controlled Markov fields with finite state space on graphs. Stochastic Models, 21(4), 847–874.
16. Kasitskaya, E. I., & Knopov, P. S. (2017). Large deviations for the method of empirical means in stochastic optimization problems with continuous time observations. Springer Optimization and Its Applications, 130, 263–276.
17. Knopov, P., & Norkin, V. (2022). Stochastic Optimization Methods for the Stochastic Storage Process Control. Springer Optimization and Its Applications, 181, 79–111
18. Knopov, P., & Korkhin, A. (2023). Dynamic models of epidemiology in discrete time taking into account processes with lag. International Journal of Dynamics and Control, 11(5), 2193–2214
19. Knopov, P. (2023). Optimization and Identification of Stochastic Systems. Cybernetics and Systems Analysis, 375–384.
20. Knopov, P. S., & Pepelyaeva, T. V. (2025). Some Applied Problems of the Theory of Controlled Random Processes. Cybernetics and Systems Analysis, 41-52.
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