Synchronisation of Timetables for Public Bus Lines Using Genetic Algorithms and Computer Simulations

  • Vitalii NaumovEmail author
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 36)


In this paper, we propose a model of the bus lines synchronisation based on simulation of the public transport system with a genetic algorithm as a tool to obtain some rational solution. The proposed approach considers stochastic nature of the public transport technological processes and provides in a short time a solution close to optimal. The total waiting time for passengers at all the nodes of a public transport network is used as the objective function in the synchronisation problem. Synchronisation is implemented due to time shifts at the schedules for public transport line; these time shifts are represented as chromosomes of a genetic algorithm. In order to evaluate the objective function, simulations of a public transport network were provided. The developed mathematical model is implemented in Python within the frame of a class library for modelling of public transport processes. A case of a public transport system of Bochnia city is applied to illustrate the procedure of synchronisation on the grounds of the developed model.


Public transport Timetables synchronisation Genetic algorithms 


  1. 1.
    Bruno, G., Improta, G., Sgalambro, A.: Models for the schedule optimisation problem at a public transit terminal. OR Spectr. 31(3), 465–481 (2009)CrossRefzbMATHGoogle Scholar
  2. 2.
    Shrivastava, P., Dhingra, S.L.: Development of coordinated schedules using genetic algorithms. J. Transp. Eng. 128(1), 89–96 (2002)CrossRefGoogle Scholar
  3. 3.
    Wu, Y., Yang, H., Tang, J., Yu, Y.: Multi-objective re-synchronizing of bus timetable: model, complexity and solution. Transp. Res. Part C 67, 149–168 (2016)CrossRefGoogle Scholar
  4. 4.
    Ceder, A., Golang, B., Tal, O.: Creating bus timetables with maximal synchronisation. Transp. Res. Part A 35(10), 913–928 (2001)Google Scholar
  5. 5.
    Wihartiko, F.D., Buono, A., Silalahi, B.P.: Integer programming model for optimizing bus timetable using genetic algorithm. IOP Conf. Ser.: Mater. Sci. Eng. 166, 012016 (2017)CrossRefGoogle Scholar
  6. 6.
    Liu, T., Ceder, A.: Synchronisation of public transport timetabling with multiple vehicle types. Transp. Res. Rec. 2539, 84–93 (2016)CrossRefGoogle Scholar
  7. 7.
    Ibarra-Rojas, O.J., López-Irarragorri, F., Rios-Solis, Y.A.: Multiperiod bus timetabling. Transp. Sci. 50(3), 805–822 (2016)CrossRefGoogle Scholar
  8. 8.
    Shen, Y., Wang, S.: An adaptive differential evolution approach for the maximal synchronisation problem of feeder buses to metro. J. Comput. Theor. Nanosci. 13(6), 3548–3555 (2016)CrossRefGoogle Scholar
  9. 9.
    Teodorović, D., Lučić, P.: Schedule synchronisation in public transit using the fuzzy ant system. Transp. Planning Technol. 28(1), 47–76 (2005)CrossRefGoogle Scholar
  10. 10.
    Wu, W., Liu, R., Jin, W.: Designing robust schedule coordination scheme for transit networks with safety control margins. Transp. Res. Part B 93A, 495–519 (2016)CrossRefGoogle Scholar
  11. 11.
    Bookbinder, J.H., Désilets, A.: Transfer optimisation in a transit network. Transp. Sci. 26(2), 106–118 (1992)CrossRefzbMATHGoogle Scholar
  12. 12.
    Dou, X., Yan, Y., Guo, X., Gong, X.: Time control point strategy coupled with transfer coordination in bus schedule design. J. Adv. Transp. 50(7), 1336–1351 (2016)CrossRefGoogle Scholar
  13. 13.
    Lee, M., Schonfeld, P.: Optimal slack time for timed transferred at transit terminal. J. Adv. Transp. 25(3), 281–308 (1991)CrossRefGoogle Scholar
  14. 14.
    Ting, C., Schonfeld, P.: Schedule coordination in a multiple hub transit network. J. Urban Planning Dev. 131(2), 112–124 (2005)CrossRefGoogle Scholar
  15. 15.
    Nesheli, M., Ceder, A., Gonzalez, V.: Real-time public-transport operational tactics using synchronized transfers to eliminate vehicle bunching. IEEE Trans. Intell. Transp. Syst. 17(11), 3220–3229 (2016)CrossRefGoogle Scholar
  16. 16.
    Naumov, V., Samchuk, G.: Class library for simulations of passenger transfer nodes as elements of the public transport system. Procedia Eng. 187, 77–81 (2017)CrossRefGoogle Scholar
  17. 17.
    Class library for modeling a public transport network. Accessed 15 July 2017

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Cracow University of TechnologyKrakówPoland

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