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p-Hub approach for the optimal park-and-ride facility location problem

Author

Listed:
  • Aros-Vera, Felipe
  • Marianov, Vladimir
  • Mitchell, John E.

Abstract

Park and Ride facilities (P&R) are car parks at which users can transfer to public transportation to reach their final destination. We propose a mixed linear programming formulation to determine the location of a fixed number of P&R facilities so that their usage is maximized. The facilities are modeled as hubs. Commuters can use one of the P&R facilities or choose to travel by car to their destinations, and their behavior follows a logit model. We apply a p-hub approach considering that users incur in a known generalized cost of using each P&R facility as input for the logit model. For small instances of the problem, we propose a novel linearization of the logit model, which allows transforming the binary nonlinear programming problem into a mixed linear programming formulation. A modification of the Heuristic Concentration Integer (HCI) procedure is applied to solve larger instances of the problem. Numerical experiments are performed, including a case in Queens, NY. Further research is proposed.

Suggested Citation

  • Aros-Vera, Felipe & Marianov, Vladimir & Mitchell, John E., 2013. "p-Hub approach for the optimal park-and-ride facility location problem," European Journal of Operational Research, Elsevier, vol. 226(2), pages 277-285.
  • Handle: RePEc:eee:ejores:v:226:y:2013:i:2:p:277-285
    DOI: 10.1016/j.ejor.2012.11.006
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    References listed on IDEAS

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    Cited by:

    1. Bruno, Giuseppe & Esposito, Emilio & Genovese, Andrea & Piccolo, Carmela, 2016. "Institutions and facility mergers in the Italian education system: Models and case studies," Socio-Economic Planning Sciences, Elsevier, vol. 53(C), pages 23-32.
    2. Etemadnia, Hamideh & Goetz, Stephan J. & Canning, Patrick & Tavallali, Mohammad Sadegh, 2015. "Optimal wholesale facilities location within the fruit and vegetables supply chain with bimodal transportation options: An LP-MIP heuristic approach," European Journal of Operational Research, Elsevier, vol. 244(2), pages 648-661.
    3. Freire, Alexandre S. & Moreno, Eduardo & Yushimito, Wilfredo F., 2016. "A branch-and-bound algorithm for the maximum capture problem with random utilities," European Journal of Operational Research, Elsevier, vol. 252(1), pages 204-212.
    4. repec:eee:ejores:v:266:y:2018:i:1:p:46-56 is not listed on IDEAS
    5. Ge, Houtian & Canning, Patrick & Goetz, Stephan & Perez, Agnes, 2015. "Assessing the Supplier Role of Selected Fresh Produce Value Chains in the United States," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205713, Agricultural and Applied Economics Association;Western Agricultural Economics Association.
    6. repec:spr:annopr:v:246:y:2016:i:1:d:10.1007_s10479-014-1704-5 is not listed on IDEAS
    7. Shahabi, Mehrdad & Unnikrishnan, Avinash, 2014. "Robust hub network design problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 70(C), pages 356-373.
    8. repec:eee:transb:v:100:y:2017:i:c:p:64-81 is not listed on IDEAS
    9. Haase, Knut & Müller, Sven, 2014. "A comparison of linear reformulations for multinomial logit choice probabilities in facility location models," European Journal of Operational Research, Elsevier, vol. 232(3), pages 689-691.
    10. Wang, Shuaian & Qu, Xiaobo, 2017. "Station choice for Australian commuter rail lines: Equilibrium and optimal fare design," European Journal of Operational Research, Elsevier, vol. 258(1), pages 144-154.

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