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A Branch-and-Cut Algorithm for the Alternative Fuel Refueling Station Location Problem with Routing

Author

Listed:
  • Okan Arslan

    (HEC Montréal and CIRRELT, Montréal, Quebec H3T 2A7 Canada)

  • Oya Ekin Karaşan

    (Department of Industrial Engineering, Bilkent University, Bilkent, 06800 Ankara, Turkey)

  • Ridha Mahjoub

    (Université Paris Dauphine, PSL Research University, CNRS [7243], LAMSADE, 75016 Paris, Île-de-France, France)

  • Hande Yaman

    (Department of Industrial Engineering, Bilkent University, Bilkent, 06800 Ankara, Turkey)

Abstract

Because of the limited range of alternative fuel vehicles (AFVs) and the sparsity of the available alternative refueling stations (AFSs), AFV drivers cooperatively deviate from their paths to refuel. This deviation is bounded by the drivers’ tolerance. Taking this behavior into account, the refueling station location problem with routing (RSLP-R) is defined as maximizing the AFV flow that can be accommodated in a road network by locating a given number of AFSs while respecting the range limitation of the vehicles and the deviation tolerance of the drivers. In this study, we develop a natural model for the RSLP-R based on the notion of length-bounded cuts, analyze the polyhedral properties of this model, and develop a branch-and-cut algorithm as an exact solution approach. Extensive computational experiments show that the algorithm significantly improves the solution times with respect to previously developed exact solution methods and extends the size of the instances solved to optimality. Using our methodology, we investigate the tradeoffs between covered vehicle flow and deviation tolerance of the drivers and present insights on deviation characteristics of drivers in a case study in California.

Suggested Citation

  • Okan Arslan & Oya Ekin Karaşan & Ridha Mahjoub & Hande Yaman, 2019. "A Branch-and-Cut Algorithm for the Alternative Fuel Refueling Station Location Problem with Routing," Transportation Science, INFORMS, vol. 53(4), pages 1107-1125, July.
    • Handle: RePEc:inm:ortrsc:v:53:y:2019:i:4:p:1107-1125
    DOI: 10.1287/trsc.2018.0869
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    References listed on IDEAS

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    Cited by:

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    2. Cao, Jianing & Han, Yuhang & Pan, Nan & Zhang, Jingcheng & Yang, Junwei, 2024. "A data-driven approach to urban charging facility expansion based on bi-level optimization: A case study in a Chinese city," Energy, Elsevier, vol. 300(C).
    3. Lange, Jan-Hendrik & Speth, Daniel & Plötz, Patrick, 2024. "Optimized demand-based charging networks for long-haul trucking in Europe," Working Papers "Sustainability and Innovation" S06/2024, Fraunhofer Institute for Systems and Innovation Research (ISI).
    4. Mahmutoğulları, Özlem & Yaman, Hande, 2023. "Robust alternative fuel refueling station location problem with routing under decision-dependent flow uncertainty," European Journal of Operational Research, Elsevier, vol. 306(1), pages 173-188.
    5. Li, Lei & Al Chami, Zaher & Manier, Hervé & Manier, Marie-Ange & Xue, Jian, 2021. "Incorporating fuel delivery in network design for hydrogen fueling stations: Formulation and two metaheuristic approaches," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    6. Xuya Zhang & Yue Wang & Dongqing Zhang, 2024. "Location-Routing Optimization for Two-Echelon Cold Chain Logistics of Front Warehouses Based on a Hybrid Ant Colony Algorithm," Mathematics, MDPI, vol. 12(12), pages 1-22, June.
    7. Kınay, Ömer Burak & Gzara, Fatma & Alumur, Sibel A., 2021. "Full cover charging station location problem with routing," Transportation Research Part B: Methodological, Elsevier, vol. 144(C), pages 1-22.
    8. Xu, Min & Meng, Qiang, 2020. "Optimal deployment of charging stations considering path deviation and nonlinear elastic demand," Transportation Research Part B: Methodological, Elsevier, vol. 135(C), pages 120-142.

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