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An optimization model for line planning and timetabling in automated urban metro subway networks. A case study

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  • Blanco, Víctor
  • Conde, Eduardo
  • Hinojosa, Yolanda
  • Puerto, Justo

Abstract

In this paper we present a Mixed Integer Linear Programming model that we developed as part of a pilot study requested by the R&D company Metrolab® in order to design tools for finding solutions for line planning and timetable situations in automated urban metro subway networks. Our model incorporates important factors in public transportation systems from both, a cost-oriented and a passenger-oriented perspective, as time-dependent demands, interchange stations, short-turns and technical features of the trains in use. The incoming flows of passengers are modeled by means of piecewise linear demand functions which are parameterized in terms of arrival rates and bulk arrivals. Decisions about frequencies, train capacities, short-turning and timetables for a given planning horizon are jointly integrated to be optimized in our model. Finally, a novel matheuristic approach is proposed to solve the problem. The results of extensive computational experiments are reported to show its applicability and effectiveness to handle real-world subway networks.

Suggested Citation

  • Blanco, Víctor & Conde, Eduardo & Hinojosa, Yolanda & Puerto, Justo, 2020. "An optimization model for line planning and timetabling in automated urban metro subway networks. A case study," Omega, Elsevier, vol. 92(C).
    • Handle: RePEc:eee:jomega:v:92:y:2020:i:c:s0305048319307492
    DOI: 10.1016/j.omega.2019.102165
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    7. Zhou, Housheng & Qi, Jianguo & Yang, Lixing & Shi, Jungang & Pan, Hanchuan & Gao, Yuan, 2022. "Joint optimization of train timetabling and rolling stock circulation planning: A novel flexible train composition mode," Transportation Research Part B: Methodological, Elsevier, vol. 162(C), pages 352-385.
    8. Nguyen, Hoa T.M. & Chow, Andy H.F. & Ying, Cheng-shuo, 2021. "Pareto routing and scheduling of dynamic urban rail transit services with multi-objective cross entropy method," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 156(C).
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