VESTNIK of Samara University. Aerospace and Mechanical EngineeringVESTNIK of Samara University. Aerospace and Mechanical Engineering2542-04532541-7533Samara National Research University762410.18287/2541-7533-2019-18-4-183-191UnknownFuzzy-controller simulation model as a tool of optimization of a limited availability ground handling system at a hub airportRomanenkoV. A.<p>Candidate of Science (Engineering), Associate Professor, <br />Associate Professor of the Department of Transportation Management and Control</p>vla_rom@mail.ruSamara National Research University211220191841831912101202021012020Copyright © 2020, VESTNIK of Samara University. Aerospace and Mechanical Engineering2020<p>The task of optimizing the optimal quantity of technological resources of a hub airports functional subsystem, executing an individual process step of ground handling, is considered. This problem is relevant to hub airports. The analysis is limited to limited availability systems in which handling of certain orders can be performed only by certain resources which are used in reference to automated and mechanical equipment, industrial equipment, personnel, etc. The optimization problem is formulated in a probabilistic statement. An approach to solving the problem is described. We suggest using a simulation computer model as an optimization tool. The model takes into account the features of passenger flows and the operating process of a hub airport and includes a fuzzy controller that reflects the logic of the airport operator who controls the ground handling process. The paper describes a model example of solving an optimization problem indicating the possibility and expedience of using a fuzzy controller as a model for the strategy of a human operator. Time dependence of the quantity of technological resources of the functional subsystem is the main result of optimization. This dependence is applicable at the stages of making decisions concerning increase of its capacity rate, operative resource management, planning staff shift work, solving a number of other tasks, especially relevant for hub airports with intense but non-uniform flows of aircraft and passengers.</p>Узловой аэропортнеполнодоступная системанечёткое управлениенечёткий регулятороптимизацияимитационная модельHub airportlimited availability systemfuzzy controlfuzzy controlleroptimizationsimulation model[1. Romanenko V.A. Modelirovanie proizvodstvennykh protsessov uzlovykh aeroportov [Hub process simulation]. Saarbrucken: LAP Lambert Academic Publishing, 2012. 296 p.][2. Romanenko V.A. Optimization of transfer air transportation system parameters considering fuzzy and stochastic uncertainties. Automation and Remote Control. 2015. V. 76, Iss. 8. P. 1500-1514. DOI: <a href='http://doi.org/10.1134/S0005117915080135'>10.1134/S0005117915080135</a>][3. Guzha E.D., Romanenko V.A., Skorokhod M.A. Optimization model of the hub airport schedule under uncertainty. IOP Conference Series: Materials Science and Engineering. 2018. V. 450. DOI: <a href='http://doi.org/10.1088/1757-899X/450/2/022023'>10.1088/1757-899X/450/2/022023</a>][4. Kacprzyk J., Pedrycz W. Springer handbook of computational intelligence. Heidelberg: Springer-Verlag, 2015. 1633 p. DOI: <a href='http://doi.org/10.1007/978-3-662-43505-2'>10.1007/978-3-662-43505-2</a>][5. Ross T.J. Fuzzy logic with engineering applications. United Kingdom: John Wiley & Sons Inc., 2010. 585 p.][6. Vasileva I.A., Romanenko V.A., Khvostova T.V. Optimization of parameters of a hub aircraft ground handling system on the basis of a fuzzy-controller simulation model. Vestnik of Samara University. Aerospace and Mechanical Engineering. 2017. V. 16, no. 1. P. 7-19. DOI: <a href='http://doi.org/10.18287/2541-7533-2017-16-1-7-19'>10.18287/2541-7533-2017-16-1-7-19</a> (In Russ.)][7. Burghouwt G., de Wit J. Temporal configurations of European airline networks. Journal of Air Transport Management. 2005. V. 11, Iss. 3. P. 185-198. DOI: <a href='http://doi.org/10.1016/j.jairtraman.2004.08.003'>10.1016/j.jairtraman.2004.08.003</a>][8. Piegat A. Fuzzy modeling and control. Heidelberg: Physica-Verlag, 2001. 728 p.][9. Mendel J.M. Uncertain rule-based fuzzy logic systems: introduction and new directions. Switzerland: Springer International Publishing, 2017. 696 p. DOI: <a href='http://doi.org/10.1007/978-3-319-51370-6'>10.1007/978-3-319-51370-6</a>][10. Mamdani E.H. Applications of fuzzy algorithms for control of simple dynamic plant. Proceedings of the Institution of Electrical Engineers. 1974. V. 121, Iss. 12. P. 1585-1588. DOI: <a href='http://doi.org/10.1049/piee.1974.0328'>10.1049/piee.1974.0328</a>]