Mathematical model construction of transport systems operation processes using fuzzy logic methods

Kozachok Larisa
Senior Lecturer, Department of Informatics and Apply Mathematics, Kharkiv National Automobile and Highway University, Ukraine, e-mail: inf_appl-math@ukr.net, ORCID ID: https://orcid.org/0000-0002-5246-4246

Kozachok Alina
Project Manager, Kharkiv Internet Marketing Agency, Ukraine, e-mail: inf_appl-math@ukr.net, ORCID ID: https://orcid.org/0000-0001-5458-6981

Cite this article:

Kozachok, L., Kozachok, A. (2021). Mathematical model construction of transport systems operation processes using fuzzy logic methods. Socio-economic research bulletin, Vìsnik socìal’no-ekonomìčnih doslìdžen’ (ISSN 2313-4569), Odessa National Economic University, Odessa, No. 3-4 (78-79), pp. 98–106.

Abstract

The article emphasizes that the improvement of management, finding and using of new methods of work optimization on the routes of urban passenger transport are the main tasks of organizing route transportation in the considered transport systems. The search for these methods is aimed at the rational use of resources, vehicles, to meet the needs of the population in travel and improve the quality of service in the implementation of passenger traffic. To ensure optimal management of work on the route of urban passenger transport, we will take as a goal the construction of a timetable for the movement of vehicles on the route, namely the creation of schedules for the release of transport and rational organization of work. The creation of these schedules takes into account the effective using use of the car fleet of enterprises, ensuring the safety of passenger transportation, and reducing the cost of services for the population. In this article, the study of passenger traffic on a certain section of the transport network and the operation of the route on it are considered using fuzzy logical methods, which gives the result of the consideration of service time minimization and maximum level of passenger satisfaction with the use of transport. In this case, the mechanism of working with inaccurate concepts in the process of finding a solution is implementing, we can imagine the input data as fuzzy sets on which logical actions are carried out. In this study, the numerical expression of the degree of satisfaction of passenger’s needs is chosen by the function of belonging to several time intervals, which is selected by the target function of finding the optimal schedule in these time intervals. The search for a solution takes into account the system of restrictions that apply to the time intervals of vehicles using. At the same time, the criterion of optimality reflects the cost of the schedule working, which includes the cost of operating time of vehicles and the cost of waiting time for passengers when traveling along the route.

Keywords

mathematical modeling; algorithmization; optimization methods; transport systems; passenger transportation.

JEL classification: C100; C190; C510; DOI: https://doi.org/10.33987/vsed.3-4(78-79).2021.98-106

UD classification: 656.072; 656.015; 519,12.176

This work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

References

1. Levkovets, P. R., Moroz, M. M., Kobyletskiy, R. V. (2007). Improving the logistics management of passenger transportation [Udoskonalennia lohistychnoho upravlinnia perevezen pasazhyriv], Visnyk KDPU imeni Mykhaila Ostrohradskoho, Vyp. 6 (47), s. 113–115 [in Ukrainian]
2. Ceder, A. (2006). Planning and Evaluation of Passenger Ferry Service in Hong Kong. Transportation, Vol. 33, pp. 133–152.
3. Ceder, A., Voß, S., Daduna, J. (2001). Efficient Timetabling and Vehicle Scheduling for Public Transport. Computer-Aided Scheduling of Public Transport. Lecture Notes in Economics and Mathematical Systems, Vol. 505, pp. 37–52. Gorbachov, P. F., Lyubiy, Ye. V. (2014). Modeling of demand for transportation of the population of small towns population by route passenger transport: monograph [Modeliuvannia popytu na perevezennia naselennia malykh mist marshrutnym pasazhirskym transportom: monohrafiia], KhNADU, Kharkiv, 257 p. [in Ukrainian]
4. Alvarez, A., Casado, S., Gonzalez Velarde, J., Pacheco, J. (2010). A computational tool for optimizing the urban public transport. Journal of Computer System Sciences International, Vol. 49 (2), pp. 244–252.
5. Leurent, F. (2011). Transport capacity constraints on the mass transit system: systemic analysis. European Transport Research Review, Vol. 3, pp. 11–21.
6. Marieke, S. van der Tuin, Pel, A. J. (2020). The disruption transport model: computing user delays resulting from infrastructure failures for multi-modal passenger & freight traffic. European Transport Research Review, Vol. 12, pp. 1–10.
7. Zadeh, L. A. (1965). Fuzzy sets. Information and Control, Vol. 8 (3), pp. 338–353.
8. Bellman, R. E., Zadeh, L. A. (1970). Decision-Making in a Fuzzy Environment. Management Science, Vol. 17, pp. 141–164.