FUZZY DECISION-MAKING PROBLEMS FOR CONTROLLING OPERATING MODES OF TECHNOLOGICAL SYSTEMS AND METHODS FOR SOLVING THEM

Statements of decision-making problems for the control of fuzzy technological objects are formalized and obtained, and methods for solving them are proposed. The object of study is the heating stations of the «hot» main oil pipeline. Since such objects are often characterized by multicriteria and often operate in conditions of unclear initial information, the tasks are formalized in the form of multicriteria decisionmaking problems in a fuzzy environment. Based on the modification of various optimality principles, new mathematical formulations of the problems to be solved were obtained and interactive heuristic algorithms for solving them were developed. The novelty of the proposed approaches to solving formalized fuzzy problems from well-known methods for solving fuzzy problems lies in the fact that problems are posed and solved without first converting them to equivalent deterministic options, which does not reduce the loss of original fuzzy information and makes it possible to obtain more adequate and effective solutions. An example is given of the practical application of the proposed approach to solving decision-making problems by implementing one of the developed algorithms when solving the problem of choosing an effective operating mode for the oil heating station of the Uzen-Samara oil pipeline at the Atyrau point.

1. Dubois D. The role of fuzzy sets indecision sciences: Old techniques and new directions / D. Dubois // Fuzzy Sets and Systems. – 2011. – Vol. 184. Р. 3-28.

2. Orazbayev B.B. Development of mathematical models and modeling of chemical engineering systems under uncertainty / B.B. Orazbayev, K.N. Orazbayeva, B.T. Utenova // Theoretical Foundations of Chemical Engineering. – 2014. – № 48(2), Р. 138-148. https://doi.org/10.1134/S0040579514020092.

3. Methods of model synthesis and multicriteria optimization of chemical-engineering systems in the fuzzy environment / B. Orazbayev, B. Assanova, M. Bakiyev et al // Journal of Theoretical and Applied Information Technology. – 2020. № 98(06). Р. 1021-1036. https://www.scopus.com/record/display.uri?eid=2-s2.0-85083790104&origin=resultslist&sort=plf-f.

4. Emelyanov S.V. Mnogokriterial'nye metody prinyatiya reshenij / S.V. Emelyanov, O.I. Larichev. – Moskva: Znanie, 1986. – 57 s.

5. The System of Models and Optimization of Operating Modes of a Catalytic Reforming Unit Using Ini-tial Fuzzy Information / B. Orazbayev, A. Zhumadillayeva, K. Orazbayeva // Energies. – 2022. – № 15(4). – Р. 1-26. https://doi.org/10.3390/en15041573.

6. Methods for Modeling and Op-timizing the Delayed Coking Process in a Fuzzy Environment / B. Orazbayev, E. Dyussembina, G. Uskenbayeva et al // Processes/ – 2023/ № 11. Р. 450. https://doi.org/10.3390/pr11020450.

7. Zaichenko YU.P. Issledovanie operatsii: Nechet. optimizatsiya: ucheb. posobie dlya vuzov po spets. «Avtomatizir. sistemy obrab. inform. i upravleniYA» i «Prikl. MatematikA» / YU.P. Zaichenko. – Kiev: Vyssh. shk., 1991. – 191 s.

8. Michaël Rademaker Aggregation of monotone reciprocal relations with application to group decision making / Michaël Rademaker, Bernard De Baets. // Fuzzy Sets and Systems. 2011. – Vol. 184. – Р. 29-51.

9. Development of mathematical models of R-1 reactor hydrotreatment unit using available information of various types / B.B. Orazbayev, Ye.A. Ospanov, K.N. Orazbayeva et al // Journal of Physics: Conference Series. – 2019. – № 1399(45) Р. 156053. https://doi.org/10.1088/1742-6596/1399/4/044024

10. Didier J. Dubois Fuzzy Sets and Systems: Theory and Applications: Acad. Press. N-York, 1980. – 393 s.

11. Rykov A.S. Sistemnyj analiz: Metody mnogokriterial'nogo vybora i nechetkoj optimi-zacii / A.S. Rykov, B.B. Orazbaev. – M.: Metallurg, 1996. – 117 s.

12. Control of Fuzzy Technologi-cal Objects Based on Mathematical Model / B. Orazbayev, Y. Ospanov, K. et al // 16-th International Conference on Control, Automation and Systems (ICCAS 2016) Oct 18-19, 2016, in HICO, Gyengju, Korea. – P. 1487-1493.

13. Mathematical mod-eling and decision-making on controlling modes of technological objects in the fuzzy environment / Y.A. Ospanov, B.B. Orazbayev, K.N. Orazbayeva et al // Proceedings of the Words Congress on intelligent Control and Automation (WCICA). Guilin, China. IEEE Catalog Number: CFP16496-ART. 2016. – Р. 103-109. https://doi.org/10.1109/WCICA.2016.7578783.

14. Mizumoto M. Comparison of fuzzy reasoning methods / M. Mizumoto, H.J. Zimmermann // Fussy Sets and Systems. – 1982. – Vol. 8, № 3. – Р. 253-283.

15. Ghodousian A. Linear optimization with an arbitrary fuzzy relational inequality / A. Ghodousian, E. Khorram // Fuzzy Sets and Systems. – 2012. – Vol. 206. Р. 89-102.

16. Dubey D. Fuzzy linear programming under interval uncertainty based on IFS representation / D. Dubey, S. Chandra, A. Mehra // Fuzzy Sets and Systems. 2012. – Vol. 188. – Р. 68-87.

17. Hydrotreating unit models based on statistical and fuzzy information / Tanirbergenova A., Orazbayev B., Ospanov Ye. et al // Periodicals of Engineering and Natural Sciences. – 2021. – № 9(4). Р. 242-258. https://doi.org/10.21533/pen.v9i4.2307.

18. Meth-ods for Developing Models in a Fuzzy Environment of Reactor and Hydrotreating Furnace of a Catalytic Re-forming Unit / Orazbayev B., Zhumadillayeva A., Orazbayeva K. et al // Applied Sciences. –2021. № 11(18). Р. 1-22. https://doi.org/10.3390/app11188317.

19. De-velopment of mathematical models and optimization of operation modes of the oil heating station of main oil pipelines under conditions of fuzzy initial information / Orazbayev B., Moldasheva Zh., Orazbayeva K. et al // Eastern-European Journal of Enterprise Technologies. 2021. – № 2(114). Р. 147-162. https://doi.org/10.15587/1729-4061.2021.244949.