A multi-optional hybrid functions entropy as a tool for transportation means repair optimal periodicity determination


The paper considers theoretical explanation and construction of some mathematical models of a transportation mean operational process in reference to maintenance optimal periodicity. The important finding is that the objectively existing engineering transportation means maintenance optimal periodicity is determined in the different from the probabilistic methods way. There is a scientifically proven explanation for the mentioned above periodicity optimization with the help of the specially introduced hybrid-optional effectiveness functions distribution. The developed doctrine uses the entropy paradigm conditional extremization approach. This contribution allows obtaining the wanted optimal periodicities sidestepping the related states probabilities determination and their further extremization. The essential breakthrough of the developed doctrine is that the optional objective effectiveness functions, in such a case, are the corresponding combinations of the intensities of the studied system’s possible transitions from state to state, which relates with the set of the considered operational options. Corresponding limit solutions for the zero-to-zero ratio indeterminate forms are analyzed. Theoretical speculations are illustrated with the example calculation experiments. The necessary diagrams are plotted.

Keyword : transportation mean, maintenance, optimal periodicity, hybrid-optional function, entropy, probability, extremization, multi-optional situation

How to Cite
Goncharenko, A. 2018. A multi-optional hybrid functions entropy as a tool for transportation means repair optimal periodicity determination. Aviation. 22, 2 (Oct. 2018), 60-66. DOI:
Published in Issue
Oct 16, 2018
Abstract Views
PDF Downloads
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.


Beljatynskij, A., Prentkovskis, O., & Krivenko, J. (2010). The experimental study of shallow flows of liquid on the airport runways and automobile roads. Transport, 25(4), 394-402.

Chepizenko, V., Kharchenko, V., & Pavlova, S. (2013). Synergy of piloted, remotely piloted and unmanned air systems in single air navigation space. Logistics and Transport, 2(18), 77-82.

Dhillon, B. S. (2006). Maintainability, maintenance, and reliability for engineers. New York: Taylor & Francis Group.

Dmitriyev, S., Koudrin, A., Labunets, A., & Kindrachuk, M. (2005). Functional coatings application for strengthening and restoration of aviation products. Aviation, 9(4), 39-45.

Fisher, C., & Hodge, S. (1986). Fisher and Hodge on bunkers. London: Lloyd’s of London Press LTD.

Gališanskis, A. (2004). Aspects of quality evaluation in aviation maintenance. Aviation, 8(3), 18-26.

Goncharenko, A. (2016, October 18-20). Several models of artificial intelligence elements for aircraft control. In IEEE 4th International Conference “Methods and Systems of Navigation and Motion Control (MSNMC)” (pp. 224-227). Kyiv, Ukraine.

Goncharenko, A. (2017a). Aircraft operation depending upon the uncertainty of maintenance alternatives. Aviation, 21(4), 126-131.

Goncharenko, A. (2017b, October 17-19). Optimal UAV maintenance periodicity obtained on the multi-optional basis. In IEEE 4th International Conference “Actual Problems of Unmanned Aerial Vehicles Developments (APUAVD)” (pp. 65-68). Kyiv, Ukraine.

Goncharenko, A. (2018a). Optimal controlling path determination with the help of hybrid optional functions distributions.Radio Electronics, Computer Science, Control, 1(44), 149-158.

Goncharenko, A. (2018b). Aeronautical and aerospace materials and structures damages to failures: Theoretical concepts. International Journal of Aerospace Engineering, 2018, Article ID 4126085, 7 pages.

Goncharenko, A. (2018c, February 20-24). Multi-optional hybrid effectiveness functions optimality doctrine for maintenance purposes. In IEEE 14th International Conference Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (TCSET-2018) (pp. 771-775). Lviv-Slavske, Ukraine.

Kasianov, V. (2013). Subjective entropy of preferences. Subjective analysis. Warsaw, Poland: Institute of aviation.

Klaas van Dokkum (2005). Ship knowledge covering ship design, construction and operation. Enkhuizen: Dokmar.

Kroes, M. J., Watkins, W. A., Delp, F., & Sterkenburg, R. (2013). Aircraft maintenance and repair. New York: McGraw-Hill, Education.

Kuiken, K. (2008a). Diesel engines for ship propulsion and power plants from 0 to 100,000 kW (1 part). Onnen: Target Global Energy Training.

Kuiken, K. (2008b). Diesel engines for ship propulsion and power plants from 0 to 100,000 kW (2 part). Onnen: Target Global Energy Training.

Le, H., & Lappas, I. (2015). Continuing airworthiness: major drivers and challenges in civil and military aviation. Aviation, 19(4), 165-170.

Nakagawa, T. (2005). Maintenance theory of reliability. London: Springer-Verlag.

Pallos, K. J. (2001). Gas turbine repair technology. Atlanta: GE Energy Services Technology, GE Power Systems.

Smirnov, N. N. et al. (1990). Technical operation of aircraft. Moscow, USSR: Transport.

Smith, D. J. (2005). Reliability, maintainability and risk. Practical methods for engineers. London: Elsevier.

Solomentsev, O., Zaliskyi, M., & Zuiev, O. (2016). Estimation of quality parameters in the radio flight support operational system. Aviation, 20(3), 123-128.

Tamarin, Y. A. (2002). Protective coatings for turbine blades. Ohio: ASM International, Materials Park.

Thian, C. V. (2015). Civil and military airworthiness challenges in Asia. Aviation, 19(2), 78-82.

Wild, T. W., & Kroes, M. J. (2014). Aircraft powerplants. New York: McGraw-Hill, Education.

Zaporozhets, O., Tokarev, V., & Attenborough, K. (2011). Aircraft Noise. Assessment, prediction and control. Glyph International, Taylor & Francis.