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A multi-objective optimisation model for train scheduling in an open-access railway market

Author

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  • Shahin Shakibaei
  • Pelin Alpkokin
  • John A. Black

Abstract

Liberalised railway markets bring into play the economic interactions amongst three dominant interest groups: passengers as system users; public entities providing the track; and private firms operating the trains. Problems that arise are multi-criteria with multi-decision-makers who may be in conflict. Our approach to this problem is similar to that of a cooperative game-theoretic non-transferable utility (NTU) to reach Pareto optimal resolutions in which the aspirations of all players are taken into account. The data are collected from the Istanbul-Ankara high-speed railway via a stated preference survey. A multi-agent system (MAS) is developed via GOLang, a programming language where the agents negotiate and interact with others based on a set of parameters such as ticket price setting and resource allocation. The results show better timetabling for trains and how to achieve higher compensation rates for the infrastructure provider by collecting higher amounts of track access charges from an optimised allocation of resources.

Suggested Citation

  • Shahin Shakibaei & Pelin Alpkokin & John A. Black, 2021. "A multi-objective optimisation model for train scheduling in an open-access railway market," Transportation Planning and Technology, Taylor & Francis Journals, vol. 44(2), pages 176-193, February.
    • Handle: RePEc:taf:transp:v:44:y:2021:i:2:p:176-193
    DOI: 10.1080/03081060.2020.1868085
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