Publications

Peer reviewed papers (JOURNAL PUBLICATIONS) (2000 - 2026)

  1. P. Sevastjanov, K. Kaczmarek, L. Dymova, L. Rutkowski. An approach to the dynamic fuzzy multi-criteria multi-currency money management on the currency exchange market, Expert Systems with Applications, 131079, https://doi.org/10.1016/j.eswa.2025.131079
  2. K. Kaczmarek, P. Sevastjanov, L. Dymova, A. Kulawik, L. Rutkowski. A fuzzy three-criteria optimization-based currency trading system with adaptive criteria shapes and money management, Engineering Applications of Artificial Intelligence, Volume 159, Part B, 8 November 2025, 111689, https://doi.org/10.1016/j.engappai.2025.111689
  3. K. Kaczmarek, L. Dymova, P. Sevastjanov, L. Rutkowski. Can volatility-dependent irregular forms of fuzzy local criteria increase the effectiveness of Forex trading models, Expert Systems with Applications, vol. 294, 15 December 2025, 128819, https://doi.org/10.1016/j.eswa.2025.128819
  4. P. Sevastjanov, K. Kaczmarek, L. Dymova, L. Rutkowski. Interpretable Forex trading models based on new technical analysis indicators and fuzzy multi-criteria optimization, Fuzzy Sets and Systems, vol. 511, 1 July 2025, 109371, https://doi.org/10.1016/j.fss.2025.109371
  5. K. Kaczmarek, P. Sevastjanov, L. Dymova, A. Kulawik, L. Rutkowski. A system of trading in the foreign exchange market based on multi-criteria optimization under Belief-Plausibility uncertainty, Applied Soft Computing, vol. 169, January 2025, 112573, https://doi.org/10.1016/j.asoc.2024.112573
  6. P. Sevastjanov, K. Kaczmarek, L. Rutkowski. A multi-model approach to the development of algorithmic trading systems for the Forex market, Expert Systems with Applications, vol. 236, February 2024, 121310, https://doi.org/10.1016/j.eswa.2023.121310
  7. P. Sevastjanov, K. Kaczmarek, L. Rutkowski. A currency trading system based on simplified models using fuzzy multi-criteria hierarchical optimization, Applied Soft Computing, vol. 147, November 2023, 110747, https://doi.org/10.1016/j.asoc.2023.110747
  8. P. Sevastjanov, L. Dymova, K. Kaczmarek. A new approach to the comparison of real, interval and fuzzy-valued intuitionistic fuzzy and Belief-Plausibility numbers, International Journal of Approximate Reasoning, vol. 152, 2023, 262-281, https://doi.org/10.1016/j.ijar.2022.11.001
  9. K. Kaczmarek, L. Dymova, P. Sevastjanov. Intuitionistic fuzzy rule-base evidential reasoning with application to the currency trading system on the Forex market, Applied Soft Computing, vol. 128, October 2022, 109522, https://doi.org/10.1016/j.asoc.2022.109522
  10. L. Dymova, K. Kaczmarek, P. Sevastjanov. An extension of rule base evidential reasoning in the interval-valued intuitionistic fuzzy setting applied to the type 2 diabetes diagnostic, Expert Systems with Applications , vol. 201, 1 September 2022, 117100, https://doi.org/10.1016/j.eswa.2022.117100
  11. P. Sevastjanov, L. Dymova, K. Kaczmarek. The new definitions of intuitionistic and belief-plausibility based local criteria with interval and fuzzy inputs applied to the multiple criteria problem of a raw material supplier selection, IEEE Access, vol. 9, 2021, 163747-163763. https://doi.org/10.1109/ACCESS.2021.3132696
  12. L. Dymova, K. Kaczmarek, P. Sevastjanov, A new approach to the bi-criteria multi-period fuzzy portfolio selection, Knowledge-Based Systems, vol. 234, 2021, 107582, https://doi.org/10.1016/j.knosys.2021.107582
  13. P. Sevastjanov, L. Dymova, K. Kaczmarek. On the Neutrosophic, Pythagorean and Some Other Novel Fuzzy Sets Theories Used in Decision Making: Invitation to Discuss, Entropy, 2021, 23(11), 1485. https://doi.org/10.3390/e23111485
  14. L. Dymova, K. Kaczmarek, P. Sevastjanov, Multiple-Criteria Fuzzy Optimization of the Heat Treatment Processes for Two Steel Rolled Products, Applied Sciences 2021, 11 (5), 2324.
  15. L. Dymova, K. Kaczmarek, P. Sevastjanov, J. Kulawik, A Fuzzy Multiple Criteria Decision Making Approach with a Complete User Friendly Computer Implementation. Entropy 2021, 23, 203. https://doi.org/10.3390/e23020203
  16. L. Dymova, K. Kaczmarek, P. Sevastjanov, Ł. Sułkowski, K. Przybyszewski, An approach to generalization of the intuitionistic fuzzy TOPSIS method in the framework of evidence theory, Journal of Artificial Intelligence and Soft Computing Research, 2021, vol. 11 (2), 157-175; https://doi.org/10.2478/jaiscr-2021-0010
  17. K. Kaczmarek, L. Dymova, P. Sevastjanov, A Simple View on the Interval and Fuzzy Portfolio Selection Problems. Entropy 2020, 22, 932; https://doi.org/10.3390/e22090932.
  18. K. Kaczmarek, L. Dymova, P. Sevastjanov, A Two Phase Method for Solving the Distribution Problem in a Fuzzy Setting, Entropy 2019, 21, 1214; https://doi.org/10.3390/e21121214
  19. L. Dymova, P. Sevastjanov, The Operations on Interval-Valued Intuitionistic Fuzzy Values in the Framework of Dempster-Shafer Theory, Information Sciences , 360 (2016), 256-272 , doi: 10.1016/j.ins.2016.04.038
  20. L. Dymova, P. Sevastjanov, K. Kaczmarek, A Forex trading expert system based on a new approach to the rule-base evidential reasoning, Expert Systems with Applications , 51 (2016), 1-13, doi:10.1016/j.eswa.2015.12.028
  21. L. Dymova, P. Sevastjanov, Generalised operations on hesitant fuzzy values in the framework of Dempster-Shafer theory, Information Sciences 311 (2015) 39-58 .
  22. L. Dymova, P. Sevastjanov, A. Tikhonenko, An interval type-2 fuzzy extension of the TOPSIS method using alpha cuts, Knowledge-Based Systems 83 (2015) 116-127
  23. L. Dymova, P. Sevastjanov, A new approach to the rule-base evidential reasoning in the intuitionistic fuzzy setting, Knowledge-Based Systems , 61 (2014) 109-117,
  24. L. Dymova, P. Sevastjanov, A. Tikhonenko, A direct interval extension of TOPSIS method, Expert Systems with Applications 40 ( 2013) 4841-4847.
  25. L. Dymova, P. Sevastjanov, M. Pilarek, A method for solving systems of linear interval equations applied to the Leontief input-output model of economics, Expert Systems with Applications 40 ( 2013) 222-230.
  26. L. Dymova, P. Sevastjanov, A. Tikhonenko, Two-criteria method for comparing real-valued and interval-valued intuitionistic fuzzy values, Knowledge-Based Systems 45 (2013) 166-173 .
  27. L. Dymova, P. Sevastjanov, A. Tikhonenko, An approach to generalization of fuzzy TOPSIS method, Information Sciences 238 (2013) 149-162 .
  28. L. Dymova, P. Sevastjanov, The operations on intuitionistic fuzzy values in the framework of Dempster-Shafer theory, Knowledge-Based Systems , 35 (2012) 132-143.
  29. L. Dymova, P. Sevastianov, K. Kaczmarek, A stock trading expert system based on the rule-base evidential reasoning using Level 2 Quotes, Expert Systems with Applications 39 (2012) 7150-7157. , doi:10.1016/j.eswa.2012.01.077
  30. P. Sevastjanov, L.Dymova, P. Bartosiewicz, A new approach to normalization of interval and fuzzy weights, Fuzzy Sets and Systems 198 (2012) 34-45 .
  31. P. Sevastianov, L. Dymova, P. Bartosiewicz, A framework for rule-base evidential reasoning in the interval setting applied to diagnosing type 2 diabetes, Expert Systems with Applications 39 (2012) 4190-4200.
  32. P. Sevastianov, L. Dymova, Fuzzy simulation and optimization of production and logistic systems, in Production Engineering and management under fuzziness. Cengiz Kahraman and Mesut Yavus (Eds.), Springer-Verlag Berlin Heidelberg, 2010, pp.249-277.
  33. L. Dymova, P. Sevastjanov , An interpretation of intuitionistic fuzzy sets in terms of evidence theory: Decision making aspect, Knowledge-Based Systems 23 (2010) 772-782.
  34. L. Dymova, P. Sevastianov, P. Bartosiewicz, A new approach to the rule-base evidential reasoning: Stock trading expert system application, Expert Systems with Applications 37 (2010) 5564-5576.
  35. P. Sevastjanov, L. Dymova, Stock screening with use of multiple criteria decision making and optimization, Omega 37 (2009) 659-671.
  36. P. Sevastjanov, L. Dymova, A new method for solving interval and fuzzy equations: linear case, Information Sciences 17 (2009) 925-937.
  37. P. Sevastianov, L. Dymova, Synthesis of fuzzy logic and Dempster-Shafer Theory for the simulation of the decision-making process in stock trading systems, Mathematics and Computers in Simulation 80 (2009) 506-521.
  38. P. Sewastjanow, L. Dymowa, On the Fuzzy Internal Rate of Return, in Fuzzy Engineering Economics with Applications. Cengiz Kahraman (Ed.), Springer-Verlag Berlin Heidelberg, 2008, p.105-128.
  39. L. Dymova, P. Sevastjanov, Fuzzy Multiobjective Evaluation of Investments with Applications, in Fuzzy Engineering Economics with Applications. Cengiz Kahraman (Ed.), Springer-Verlag Berlin Heidelberg, 2008, p.243-287.
  40. P. Sevastianov. Numerical methods for interval and fuzzy number comparison based on the probabilistic approach and Dempster-Shafer theory, Information Sciences 177 (2007) 4645-4661.
  41. P. Sevastjanov, P. Figat, Aggregation of aggregating modes in MCDM: Synthesis of Type 2 and Level 2 fuzzy sets, Omega , Volume 35, Issue 5, October 2007, Pages 505-523.
  42. P. Sevastjanov, P. Rog. Two-objective method for crisp and fuzzy interval comparison in optimization, Computers and Operation Research, 33 (2006), pp. 115-131.
  43. L. Dymova, P.Sevastjanov, D. Sevastjanov, MCDM in a Fuzzy Setting: Investment Projects Assessment Application, Int. Journal of Production Economy , 100 (2006) 10-29.
  44. L. Dymova, P.Sevastjanov, D. Sevastjanov, Fuzzy capital budgeting: investment project evaluation and optimization, pp. 205-228. Part II, chapter 2 in Springer book "Fuzzy applications in industrial engineering, 2006."
  45. P. Sewastianow, P. Róg, A Probability Approach to Fuzzy and Crisp Intervals Ordering, TASK Quarterly, vol. 7, Special Issue ""Artifical and Computational Intelligence"", 1 (2003), pp. 142-158."
  46. P. Sewastianow, P. Róg, Fuzzy modeling of manufacturing and logistic systems, Mathematics and Computers in Simulation , 63 (2003), pp. 569-585
  47. P. Sewastianow, M, Jończyk, Bicriterial fuzzy portfolio selection, Operations Research and Decisions, 4 (2003), pp. 149-165.
  48. L. Dymova, D. Sevastiynov, P. Sevastiynov, Application of fuzzy sets theory methods for the evaluation of investment efficiency parameters. Fuzzy economic review, Vol. V, 1(2000), pp. 77 - 87.

Books

  1. N. Diligencki, L. Dymova, P. Sevastjanov, Fuzzy modeling and multiple-criteria optimization of production systems under uncertainty conditions: Technology, economics, ecology, Ed. Mechanical Engineering, Moscow, 2004 (in Russian)).
  2. P. Sevastjanov, Financial Mathematics and investment models, Grodno, Grodno State University Publishing House, 2001 (in Russian).
  3. P. Sevastjanov, Financial Mathematics and investment models, Grodno, Grodno State University Publishing House, 2001 (in Russian).).

The peer reviewed papers in conferences proceedings

  1. Sevastjanov P., Redefinition of Intuitionistic Fuzzy TOPSIS Method in the Framework of Evidence Theory. ICAISC 2020. LNCS, 2020 vol 12415, 351-360.
  2. Ludmila Dymova and Pavel Sevastjanov, A new method for solving nonlinear interval and fuzzy equations, LNCS, 2018 v. 10778, 371-380.
  3. Ludmila Dymova, Pavel Sevastjanow, Andrzej Pownuk and Vladik Kreinovich, Practical Need for Equation-Type Interval Equations and for Their Extended-Zero Solutions, LNCS, 2018 v. 10778, 412-421
  4. L. Dymova, K. Kaczmarek, P. Sevastianov, A comparative study of two novel approaches to the rule-base evidential reasoning, ICAISC 2017, LNCS (LNAI), vol. 10245, pp. 231-240, Springer, Cham (2017). DOI: 10.1007/978-3-319-59063-9_21
  5. "L. Dymova, P. Sevastjanov, A. Tikhonenko, ""The TOPSIS Method in the Interval Type-2 Fuzzy Setting"", PPAM, Lecture Notes in Computer Science, 2016, 9574, 445-454."
  6. L. Dymova, P. Sevastianov, K. Kaczmarek, A new approach to the rule-base evidential reasoning with application, Lecture Notes in Artificial Intelligence, 2015, 271-282.
  7. L. Dymova, P. Sevastjanov, K. Tkacz, T. Cheherava, A new measure of conflict and hybrid combination rules in the evidence theory, Lecture Notes in Artificial Intelligence, 2014, 411-422.
  8. L. Dymova, P. Sevastjanov, The Definition of Interval-Valued Intuitionistic Fuzzy Sets in the Framework of Dempster-Shafer Theory, PPAM (2), 2013, 634-643.
  9. L. Dymova, P. Sevastjanov, K. Tkacz, The use of Intuitionistic Fuzzy Values in Rule-Bas Evidential Reasononing, ICAISC 2013, Part 1, LNAI 7894, pp. 247-258, 2013.
  10. "L. Dymova, P. Sevastjanov, K. Tkacz, ""The use of belief intervals in operations on intuitionistic fuzzy values"", Lecture Notes in Artificial Intelligence , 2012, 7267, P.1, 229-236."
  11. "L. Dymova, P. Sevastjanov, A. Tikhonenko, ""A new method for comparing interval-valued intuitionistic fuzzy values"", Lecture Notes in Artificial Intelligence , 2012, 7267, P.1, 221-228."
  12. "L. Dymova, M. Pilarek, ""Organizing calculations in algorithms for solving systems of interval linear equations using the ""interval extended zero"" method, Lecture Notes in Computer Science"", 2012, 7204, 439-446."
  13. "P. Sevastjanov, A. Tikhonenko ,""Direct interval extension of TOPSIS method"", Lecture Notes in Computer Science, 2012, 7204, 404-512."
  14. "P. Sevastjanov, P. Bartosiewicz, K. Tkacz, ""A method for comparing intervals with interval bounds"", Lecture Notes in Computer Science, 2012, 7204, 496-503."
  15. Ludmila Dymova, Pavel Sevastjanov, An interpretation of Intuitionistic Fuzzy sets in the framework of the Dempster-Shafer theory, 10th Int. Conf. Artificial Intelligence and Soft Computing, ICAISC, 2010, LNAI 6114, Part II, pp. 229-240
  16. Pavel Sevastjanov, Pavel Bartosiewicz, Kamil Tkacz, The normalization of the Dempster's rule of combination, 10th Int. Conf. Artificial Intelligence and Soft Computing, ICAISC, 2010, LNAI 6114, Part II, pp. 229-240.
  17. Pavel Sevastjanov, Pavel Bartosiewicz, Kamil Tkacz, A new method for normalization of interval weights, Paralel Processing and Applied Mathematics, 8th Int. Conf.Springer Verlag, 2010, LNCS 6068, Part II, pp.466-474.
  18. L. Dymova, I. Róg, P. Sevastjanov, A new method for decision making in the intuitionistic fuzzy setting, Proceedings 9th Int. Conf. Artificial Intelligence and Soft Computing, ICAISC, 2008, pp. 229-240.
  19. P. Sevastjanov , L. Dymova, Fuzzy solution of interval linear equations, , Paralel Processing and Applied Mathematics, 7th Int. Conf.Springer Verlag, 2008, LNCS 4967, pp.1392-1399.
  20. P. Sevastianov, Interval comparison based on Dempster-Shafer theory of evidence, Paralel Processing and Applied Mathematics, 5th Int. Conf.Springer Verlag, 2004, LNCS3019, pp.668-675.
  21. P. Sevastianov, L. Dymova, M. Dolata, The fuzzy decision of transportation problem. Proceedings of Int., Conf. Modelling and Simulation. Minsk, 2004, pp. 308-311.
  22. L. Dymova, M. Gonera, P. Sewastianow, R. Wyrzykowski, New method for interval extension of Leontief's input-output model with use of parallel programming, Proceedings of Int. Conf. on Fuzzy Sets and Soft Computing in Economics and Finance, St. Petersburg, Russia, 2004, pp. 549-556.
  23. P. Sevastianov, P. Rozenberg.Optimal investment using technical analysis and fuzzy logic. Proceedings of Int. Conf. on Fuzzy Sets and Soft Computing in Economics and Finance, St. Petersburg, Russia, 2004, pp. 415-422.
  24. P. Sewastianow, M. Joñczyk, Comparative study of aggregation methods in bicriterial fuzzy portfolio selection. Proceedings of Int. Conf. on Fuzzy Sets and Soft Computing in Economics and Finance, St. Petersburg, Russia, 2004, pp. 484-492.
  25. P. Sewastianow, P. Róg, Fuzzy Optimization Using Direct Crisp and Fuzzy Interval Comparison, Rutkowski L., Kacprzyk J. (eds) Advances in Soft Computing (Physica-Verlag, 2003), pp.317-321.
  26. P. Sevastjanov, P. Rog, A. Venberg, A method for simulating of manufacturing systems using fuzzy intervals. New Information Technologies: Proceedings of the Fifth International Conference, Minsk, Belarus, Oct. 29-31, 2002, Minsk: BSEU, 2002, V. 1, pp.39-44.
  27. L. Dymova, P. Sevastjanov, P. Figat, The method and software for multiobjective decision making. New Information Technologies: Proceedings of the Fifth International Conference, Minsk, Belarus, Oct. 29-31, 2002. Minsk: BSEU, 2002, V. 1, pp.45-48.
  28. L. Dymova, P. Róg, P. Sevastianov, Hyperfuzzy estimations of financial parameters. 2nd Int. Conf. Mathematical Methods in Finance and Econometrics, Belarus State University, Minsk, Belarus, June 20 - 22, 2002, pp. 78-84.
  29. P. Sevastianov, A. Venberg, Constructive method for fuzzy interval comparison in optimization tasks. Information Networks, Systems and Technologies, Proceedings of VII International Conference, Minsk, 2001, pp. 52-57. (in Russian)
  30. P. Sewastianow, P. Róg, A. Venberg, The Constructive Numerical Method of Interval Comperison, Wyrzykowski R., Dongara J., Paprzycki M., Waœniewski J. (Eds.), Parallel Processing and Applied Mathematics, Springer, 2001, s. 756-761.
  31. L. Dymova, P. Sevastianov, T. Chegerova, D. Sevastianov, Fuzzy-Based Multicriterial optimization of Economic and Ecological System. Information Networks, Systems and Technologies, Proceedings of VII International Conference, Minsk, 2001, pp. 139-143. (in Russian).