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The design of interurban bus networks in city centers

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  • Roca-Riu, Mireia
  • Estrada, Miquel
  • Trapote, César

Abstract

This paper proposes a bilevel formulation for solving the Bus Network Design Problem (BNDP) of interurban services entering a major city. It is focused in interurban services because it is a growing problem in most of major cities, yet new in the literature. The layout of interurban bus routes and the locations of transfer stations in the main city are the key factors to provide a competitive public transportation service to commuters in a metropolitan area. The number of commuters in huge urban concentrations is growing due to the difficulties of living near the city center. The objective function of the first level is defined with the aim of reducing user and agency costs. In the second level the performance of users is addressed. Furthermore, a local search method based on the Tabu Search algorithm was carried out to guide the exploration in the solution domain. The results obtained in a set of test problems have demonstrated that the restart parameters of the algorithm play a significant role in the efficiency of the algorithm. Finally, implementation in the large network of Barcelona (Spain) reduces the total cost by 5% with regard to the present situation.

Suggested Citation

  • Roca-Riu, Mireia & Estrada, Miquel & Trapote, César, 2012. "The design of interurban bus networks in city centers," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(8), pages 1153-1165.
    • Handle: RePEc:eee:transa:v:46:y:2012:i:8:p:1153-1165
    DOI: 10.1016/j.tra.2012.05.011
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    References listed on IDEAS

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    1. Wei Fan & Randy B. Machemehl, 2008. "A Tabu Search Based Heuristic Method for the Transit Route Network Design Problem," Lecture Notes in Economics and Mathematical Systems, in: Mark Hickman & Pitu Mirchandani & Stefan Voß (ed.), Computer-aided Systems in Public Transport, pages 387-408, Springer.
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    Cited by:

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    3. Philipp Heyken Soares, 2021. "Zone-based public transport route optimisation in an urban network," Public Transport, Springer, vol. 13(1), pages 197-231, March.
    4. Nocera, Silvio & Fabio, Alberto & Cavallaro, Federico, 2020. "The adoption of grid transit networks in non-metropolitan contexts," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 256-272.
    5. Yang, Xu-Hua & Chen, Guang & Chen, Sheng-Yong & Wang, Wan-Liang & Wang, Lei, 2014. "Study on some bus transport networks in China with considering spatial characteristics," Transportation Research Part A: Policy and Practice, Elsevier, vol. 69(C), pages 1-10.
    6. Ibarra-Rojas, O.J. & Delgado, F. & Giesen, R. & Muñoz, J.C., 2015. "Planning, operation, and control of bus transport systems: A literature review," Transportation Research Part B: Methodological, Elsevier, vol. 77(C), pages 38-75.
    7. Pternea, Moschoula & Kepaptsoglou, Konstantinos & Karlaftis, Matthew G., 2015. "Sustainable urban transit network design," Transportation Research Part A: Policy and Practice, Elsevier, vol. 77(C), pages 276-291.
    8. Sunhyung Yoo & Jinwoo Brian Lee & Hoon Han, 2023. "A Reinforcement Learning approach for bus network design and frequency setting optimisation," Public Transport, Springer, vol. 15(2), pages 503-534, June.

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