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On the design of public infrastructure systems with elastic demand

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  • Daganzo, Carlos F.

Abstract

This paper considers the optimization of public infrastructure systems, recognizing that these systems serve multiple user classes. Example application domains include: public transportation systems, electricity distribution grids, urban water distribution systems, and maintenance of pavement and bridge systems. Under the guidance of a policy-making body, the analyst chooses both the system design, including its layout and control, and the prices to be charged for the service. The goal of the optimization is to maximize society’s welfare recognizing that the system’s performance will in general depend on the system’s demand, and vice versa.

Suggested Citation

  • Daganzo, Carlos F., 2012. "On the design of public infrastructure systems with elastic demand," Transportation Research Part B: Methodological, Elsevier, vol. 46(9), pages 1288-1293.
    • Handle: RePEc:eee:transb:v:46:y:2012:i:9:p:1288-1293
    DOI: 10.1016/j.trb.2012.06.005
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    References listed on IDEAS

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    1. Robert Cervero & Mark Hansen, 2002. "Induced Travel Demand and Induced Road Investment: A Simultaneous Equation Analysis," Journal of Transport Economics and Policy, University of Bath, vol. 36(3), pages 469-490, September.
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    Cited by:

    1. Hörcher, Daniel & Tirachini, Alejandro, 2021. "A review of public transport economics," Economics of Transportation, Elsevier, vol. 25(C).
    2. Sathaye, Nakul & Kelley, Scott, 2013. "An approach for the optimal planning of electric vehicle infrastructure for highway corridors," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 59(C), pages 15-33.
    3. Ouyang, Yanfeng & Nourbakhsh, Seyed Mohammad & Cassidy, Michael J., 2014. "Continuum approximation approach to bus network design under spatially heterogeneous demand," Transportation Research Part B: Methodological, Elsevier, vol. 68(C), pages 333-344.
    4. Sathaye, Nakul, 2014. "The optimal design and cost implications of electric vehicle taxi systems," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 264-283.
    5. Luigi Moccia & Duncan W. Allen & Eric C. Bruun, 2018. "A technology selection and design model of a semi-rapid transit line," Public Transport, Springer, vol. 10(3), pages 455-497, December.
    6. Luigi Moccia & Duncan W. Allen & Gilbert Laporte & Andrea Spinosa, 2022. "Mode boundaries of automated metro and semi-rapid rail in urban transit," Public Transport, Springer, vol. 14(3), pages 739-802, October.
    7. Amirgholy, Mahyar & Shahabi, Mehrdad & Gao, H. Oliver, 2017. "Optimal design of sustainable transit systems in congested urban networks: A macroscopic approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 103(C), pages 261-285.
    8. Rehak, David & Markuci, Jiri & Hromada, Martin & Barcova, Karla, 2016. "Quantitative evaluation of the synergistic effects of failures in a critical infrastructure system," International Journal of Critical Infrastructure Protection, Elsevier, vol. 14(C), pages 3-17.
    9. Sivakumaran, Karthik & Li, Yuwei & Cassidy, Michael & Madanat, Samer, 2014. "Access and the choice of transit technology," Transportation Research Part A: Policy and Practice, Elsevier, vol. 59(C), pages 204-221.
    10. Moccia, Luigi & Giallombardo, Giovanni & Laporte, Gilbert, 2017. "Models for technology choice in a transit corridor with elastic demand," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 733-756.
    11. Luigi Moccia & Duncan W. Allen & Gilbert Laporte, 2020. "A spatially disaggregated model for the technology selection and design of a transit line," Public Transport, Springer, vol. 12(3), pages 647-691, October.
    12. Zetina, Carlos Armando & Contreras, Ivan & Cordeau, Jean-François, 2019. "Profit-oriented fixed-charge network design with elastic demand," Transportation Research Part B: Methodological, Elsevier, vol. 127(C), pages 1-19.

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