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Urban rapid transit network capacity expansion

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  • Marí­n, íngel
  • Jaramillo, Patricia

Abstract

This paper examines a multi-period capacity expansion problem for rapid transit network design. The capacity expansion is realized through the location of train alignments and stations in an urban traffic context by selecting the time periods. The model maximizes the public transportation demand using a limited budget and designing lines for each period. The location problem incorporates the user decisions about mode and route. The network capacity expansion is a long-term planning problem because the network is built over several periods, in which the data (demand, resource price, etc.) are changing like the real problem changes. This complex problem cannot be solved by branch and bound, and for this reason, a heuristic approach has been defined in order to solve it. Both methods have been experimented in test networks.

Suggested Citation

  • Marí­n, íngel & Jaramillo, Patricia, 2008. "Urban rapid transit network capacity expansion," European Journal of Operational Research, Elsevier, vol. 191(1), pages 45-60, November.
    • Handle: RePEc:eee:ejores:v:191:y:2008:i:1:p:45-60
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    References listed on IDEAS

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    1. Gilbert Laporte & Juan Mesa & Francisco Ortega & Ignacio Sevillano, 2005. "Maximizing Trip Coverage in the Location of a Single Rapid Transit Alignment," Annals of Operations Research, Springer, vol. 136(1), pages 49-63, April.
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    Cited by:

    1. Lebing Wang & Jian Gang Jin & Gleb Sibul & Yi Wei, 2023. "Designing Metro Network Expansion: Deterministic and Robust Optimization Models," Networks and Spatial Economics, Springer, vol. 23(1), pages 317-347, March.
    2. Martins de Sá, Elisangela & Contreras, Ivan & Cordeau, Jean-François, 2015. "Exact and heuristic algorithms for the design of hub networks with multiple lines," European Journal of Operational Research, Elsevier, vol. 246(1), pages 186-198.
    3. Laporte, G. & Mesa, J.A. & Ortega, F.A. & Perea, F., 2011. "Planning rapid transit networks," Socio-Economic Planning Sciences, Elsevier, vol. 45(3), pages 95-104, September.
    4. Torres-Rincón, Samuel & Sánchez-Silva, Mauricio & Bastidas-Arteaga, Emilio, 2021. "A multistage stochastic program for the design and management of flexible infrastructure networks," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    5. An, Kun & Lo, Hong K., 2016. "Two-phase stochastic program for transit network design under demand uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 84(C), pages 157-181.
    6. Szeto, W.Y. & Wu, Yongzhong, 2011. "A simultaneous bus route design and frequency setting problem for Tin Shui Wai, Hong Kong," European Journal of Operational Research, Elsevier, vol. 209(2), pages 141-155, March.
    7. Majid Taghavi & Kai Huang, 2016. "A multi‐stage stochastic programming approach for network capacity expansion with multiple sources of capacity," Naval Research Logistics (NRL), John Wiley & Sons, vol. 63(8), pages 600-614, December.
    8. Luis Cadarso & Ángel Marín, 2017. "Improved rapid transit network design model: considering transfer effects," Annals of Operations Research, Springer, vol. 258(2), pages 547-567, November.
    9. Fragkos, Ioannis & Cordeau, Jean-François & Jans, Raf, 2021. "Decomposition methods for large-scale network expansion problems," Transportation Research Part B: Methodological, Elsevier, vol. 144(C), pages 60-80.
    10. Cadarso, Luis & Escudero, Laureano F. & Marín, Angel, 2018. "On strategic multistage operational two-stage stochastic 0–1 optimization for the Rapid Transit Network Design problem," European Journal of Operational Research, Elsevier, vol. 271(2), pages 577-593.
    11. Majid Taghavi & Kai Huang, 2020. "A Lagrangian relaxation approach for stochastic network capacity expansion with budget constraints," Annals of Operations Research, Springer, vol. 284(2), pages 605-621, January.
    12. Andreas Bärmann & Alexander Martin & Hanno Schülldorf, 2017. "A Decomposition Method for Multiperiod Railway Network Expansion—With a Case Study for Germany," Transportation Science, INFORMS, vol. 51(4), pages 1102-1121, November.

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