Identification of preferences in decision support systems

• Autorzy: Beskorovainyi V. , Berezovskyi H.
• Języki publikacji: EN

Abstrakty

EN

In this work we obtained the solution of increasing of adequacy of models of multicriteria evaluation for the project and management decision support systems. Modifications of the utility functions of partial criteria and the procedure for calculating their values are proposed, which makes it possible to improve the accuracy of approximation of the preferences of the person making the decision, as well as significantly reduce the time for calculating their values. For the parametric synthesis of universal multicriteria estimation models based on the Kolmogorov-Gabor polynomial, an improvement in the method of comparator identification by calculating the Chebyshev point and the discrepancy vector is proposed.

Słowa kluczowe

EN

decision support; multi-criteria optimization; utility function of partial criteria

• Wydawca: Polish Academy of Sciences, Branch in Lublin
• Czasopismo: ECONTECHMOD : An International Quarterly Journal on Economics of Technology and Modelling Processes
• Rocznik: 2017
• Tom: Vol. 6, No 4
• Strony: 15--20
• Opis fizyczny: Bibliogr. 20 poz., wykr., wz.

Twórcy

autor

Beskorovainyi V.

• Kharkiv National University of Radio Electronics, Nauka Ave, 14, Kharkov, 61166, Ukraine

autor

Berezovskyi H.

• Kharkiv National University of Radio Electronics, Nauka Ave, 14, Kharkov, 61166, Ukraine

Bibliografia

• 1. Greco S., Ehrgott M. 2016. Multiple Criteria Decision Analysis – State of the Art Surveys. New York: Springer, 1346.
• 2. Kaliszewski I., Miroforidis I., Podkopaev D. 2016. Multiple Criteria Decision Making by Multiobjective Optimization – A Toolbox. New York: Springer, 142.
• 3. Kaliszewski I., Kiczkowiak T., Miroforidis J. 2016. Mechanical design, Multiple Criteria Decision Making and Pareto optimality gap. Engineering Computations. Vol. 33(3), 876-895.
• 4. Petrov E. G., Pisklakova V. P., Beskorovainyi V. V. 1992. Geographically distributed service systems. Кiev: Тehnika, 208 (in Russian).
• 5. Beskorovainyi V. V., Podoliaka K. E. 2015. Development model of multicriteria problem for reengineering topological structure of large-scale monitoring system. Eastern-European Journal of Eenterprise Technologies. Vol. 4(76), 49–55 (in Russian).
• 6. Beskorovainyi V. V. and Podoliaka K. E. 2015. Reengineering the topological structure of large-scale monitoring systems. Econtechmod. An international quarterly journal. Vol. 4 (3), 13–18.
• 7. Zhivitskaya H. 2014. Topological properties and methodology of research of complex logistic systems efficiency. Econtechmod. An international quarterly journal. Vol. 3(3), 23–32.
• 8. Karpukhin A., Gritsiv D., Tkachenko A. 2014. Mathematical simulation of infocommunication networks Applying chaos theory. Econtechmod. An international quarterly journal. Vol. 3(3), 33–42.
• 9. Оvezgeldiev A. O., Petrov E. G., Petrov K. E. 2002. Synthesis and identification of multifactorial models for estimation and optimization. Кiev: Naukova dumka, 164 (in Russian).
• 10. Beskorovainyi V. V., Petrov E. G., Trofimenko I. V. 2006. Solving method the general problem of comparative identification for models of multifactorial evaluation. Bionica Intellecta, № 2 (65), 3–7 (in Russian).
• 11. Kruchkovskyi V. V., Petrov E. G., Sokolova N. A., Hodakov V. E. 2013. Introduction to the normative theory of decision-making. – Herson: Grin D.S., 284 (in Russian).
• 12. Raskin L. G., Seraja O. V. 2008. Fuzzy Mathematics. Fundamentals of the theory. Apps. Kharkiv: Parus, 352 (in Russian).
• 13. Ljung L. 1991. System Identification. Theory for the user. Мoskva: Nauka, 432 (in Russian).
• 14. Beskorovainyi V. V., Soboleva E. V. 2010. Identifying the locale value of multifactor options using S-shaped functions. Bionica Intellecta. №1, 50 – 54 (in Russian).
• 15. Petrov E. G., Bulavin D. A., Petrov K. E. 2004. Solution problem of structural-parametric identification individual multifactor estimation model by the method of group accounting of arguments. Automated Control Systems and Automation Devices. Vol. 129, 4–13 (in Russian).
• 16. Beskorovainyi V. V., Trofimenko I. V. 2006. Structural-parametric identification of models for multi-factor estimation. Systems of Arms and Military Equipment. № 3 (7), 56 – 59 (in Ukrainian).
• 17. Beskorovainyi V. V., Podoliaka K. E. 2016. Selection multicriteria decision in process of reengineering the topological structure of large-scale monitoring systems . Information Processing Systems. № 5 (142), 80–86 (in Russian).
• 18. Beskorovainyi V. V., Podoliaka K. E. Moskalenko A. S. 2016. Multifactor estimation of variants of reengineering of large-scale objects on the basis of comparator identification. Electro-technical and computer systems. № 23 (99), 192–200 (in Russian).
• 19. Beskorovainyi V. V., Moskalenko A. S. 2016. Formation and selection of solutions in projects for optimization of large-scale objects. Technology of instrument making. №2, 11–14 (inRussian).
• 20. Beskorovainyi V. V., Samirez O. N., Nastenko S. V. 2016. Methods for determining subsets of effective solutions for the design of large-scale objects. Technology of instrument making. №2, 7–10 (in Russian).

Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).