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Optimizing Urban Public Transportation with Ant Colony Algorithm

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Computational Collective Intelligence (ICCCI 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9875))

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Abstract

Transport system in most cities has some problems and should be optimized. In particular, timetable of the city public transportation needs to be changed. Metaheuristic methods for timetabling were considered the most efficient. Ant algorithm was chosen as one of these methods. It was adapted for optimization of an urban public transport timetable. A timetable for one bus route in the city of Tomsk, Russia was created on the basis of the developed software. Different combinations of parameters in ant algorithm allow obtaining new variants of the timetable that better fit passengers’ needs.

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Author information

Authors and Affiliations

  1. Tomsk Polytechnic University, Lenin Avenue 30, 634050, Tomsk, Russian Federation

    Elena Kochegurova & Ekaterina Gorokhova

Authors
  1. Elena Kochegurova
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  2. Ekaterina Gorokhova
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Corresponding author

Correspondence to Elena Kochegurova .

Editor information

Editors and Affiliations

  1. Wrocław University of Technology, Wrocław, Poland

    Ngoc-Thanh Nguyen

  2. Aristotle University of Thessaloniki, Thessaloniki, Greece

    Lazaros Iliadis

  3. Department of Forestry and Management, Democritus University of Thrace, Orestiada, Thrace, Greece

    Yannis Manolopoulos

  4. Wrocław University of Technology, Wrocław, Poland

    Bogdan Trawiński

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Kochegurova, E., Gorokhova, E. (2016). Optimizing Urban Public Transportation with Ant Colony Algorithm. In: Nguyen, NT., Iliadis, L., Manolopoulos, Y., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2016. Lecture Notes in Computer Science(), vol 9875. Springer, Cham. https://doi.org/10.1007/978-3-319-45243-2_45

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  • DOI: https://doi.org/10.1007/978-3-319-45243-2_45

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-45242-5

  • Online ISBN: 978-3-319-45243-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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