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Alternative-Fuel Vehicle Adoption in Service Fleets: Impact Evaluation Through Optimization Modeling

Author

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  • Mesut Yavuz

    (Culverhouse College of Commerce, University of Alabama, Tuscaloosa, Alabama 35487)

  • Ismail Çapar

    (Industrial Distribution Program, Texas A&M University, College Station, Texas 77843)

Abstract

This paper introduces a new rich vehicle routing problem faced by companies that consider alternative-fuel vehicle (AFV) adoption into a service fleet consisting of gasoline or diesel vehicles. The service operation addressed here differs from delivery operations in that a vehicle has to stop for extended periods of time while its driver serves customers. We discuss measuring the impact of AFV adoption on fleet operations from multiple perspectives and formulate four objective functions to represent the defined performance metrics in a generalized mixed-integer linear programming model. The model can accommodate various AFV types with respect to driving range, refueling time, and availability of refueling stations. We develop a variable neighborhood search heuristic to solve large-scale problems efficiently. Results from the research show that the classical vehicle routing objective of minimizing total vehicle miles traveled does not work well in this emerging problem; instead, an objective such as minimizing carbon emissions or fuel costs provides more desirable solutions. The results also show that in service fleets, refueling time has lesser impact on fleet performance compared to service station availability or vehicle range. From a managerial standpoint, this indicates that investment in range extension or establishing service stations is more important than investment in faster refueling capability.

Suggested Citation

  • Mesut Yavuz & Ismail Çapar, 2017. "Alternative-Fuel Vehicle Adoption in Service Fleets: Impact Evaluation Through Optimization Modeling," Transportation Science, INFORMS, vol. 51(2), pages 480-493, May.
    • Handle: RePEc:inm:ortrsc:v:51:y:2017:i:2:p:480-493
    DOI: 10.1287/trsc.2016.0697
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    References listed on IDEAS

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    Cited by:

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    2. Zhan, Xingbin & Szeto, W.Y. & (Michael) Chen, Xiqun, 2022. "A simulation–optimization framework for a dynamic electric ride-hailing sharing problem with a novel charging strategy," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 159(C).
    3. Maximilian Schiffer & Michael Schneider & Grit Walther & Gilbert Laporte, 2019. "Vehicle Routing and Location Routing with Intermediate Stops: A Review," Transportation Science, INFORMS, vol. 53(2), pages 319-343, March.
    4. Erfan Ghorbani & Mahdi Alinaghian & Gevork. B. Gharehpetian & Sajad Mohammadi & Guido Perboli, 2020. "A Survey on Environmentally Friendly Vehicle Routing Problem and a Proposal of Its Classification," Sustainability, MDPI, vol. 12(21), pages 1-71, October.
    5. Asghari, Mohammad & Mirzapour Al-e-hashem, S. Mohammad J., 2021. "Green vehicle routing problem: A state-of-the-art review," International Journal of Production Economics, Elsevier, vol. 231(C).
    6. Koyuncu, Işıl & Yavuz, Mesut, 2019. "Duplicating nodes or arcs in green vehicle routing: A computational comparison of two formulations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 605-623.
    7. Schücking, Maximilian & Jochem, Patrick, 2021. "Two-stage stochastic program optimizing the cost of electric vehicles in commercial fleets," Applied Energy, Elsevier, vol. 293(C).
    8. Seyfi, Majid & Alinaghian, Mahdi & Ghorbani, Erfan & Çatay, Bülent & Saeid Sabbagh, Mohammad, 2022. "Multi-mode hybrid electric vehicle routing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 166(C).
    9. Neves-Moreira, Fábio & Amorim-Lopes, Mário & Amorim, Pedro, 2020. "The multi-period vehicle routing problem with refueling decisions: Traveling further to decrease fuel cost?," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).

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