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Obtaining the optimal fleet mix: A case study about towing tractors at airports

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  • Du, Jia Yan
  • Brunner, Jens O.
  • Kolisch, Rainer

Abstract

Planes do not have a reverse gear. Hence, they need to be towed by tractors when leaving the gate. Towing tractors differ with respect to investment as well as variable costs and plane type compatibility. We propose a model which addresses the problem of a cost minimal fleet composition to support towing service providers in their strategic investment decisions. The model takes into account a maximum lifetime, a minimum duration of use, an overhaul option and a sell option. In a case study with a major European airport (our cooperating airport) we generate a multi-period fleet investment schedule. Furthermore, we introduce a 4-step approach for demand aggregation based on flight schedule information. We analyze the impact of demand variation, flight schedule disruptions and cost structure on the optimal buy, overhaul and sell policy. The scenario analyses demonstrate the robustness of the investment schedule with respect to these factors. Ignoring the existing fleet, a green field scenario reveals saving potentials of more than 5% when applying this model.

Suggested Citation

  • Du, Jia Yan & Brunner, Jens O. & Kolisch, Rainer, 2016. "Obtaining the optimal fleet mix: A case study about towing tractors at airports," Omega, Elsevier, vol. 64(C), pages 102-114.
    • Handle: RePEc:eee:jomega:v:64:y:2016:i:c:p:102-114
    DOI: 10.1016/j.omega.2015.11.005
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    References listed on IDEAS

    as
    1. Du, Jia Yan & Brunner, Jens O. & Kolisch, Rainer, 2014. "Planning towing processes at airports more efficiently," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 70(C), pages 293-304.
    2. Said Salhi & M. Sari & Doudja Saïdi-Kabeche & Nasséra Touati, 1992. "Adaptation of some Vehicle Fleet Mix heuristics," Post-Print halshs-00166301, HAL.
    3. Schick, GJ & Stroup, JW, 1981. "Experience with a multi-year fleet planning model," Omega, Elsevier, vol. 9(4), pages 389-396.
    4. C Burt & L Caccetta & P Welgama & L Fouché, 2011. "Equipment selection with heterogeneous fleets for multiple-period schedules," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(8), pages 1498-1509, August.
    5. Peiling Wu & Joseph C. Hartman & George R. Wilson, 2005. "An Integrated Model and Solution Approach for Fleet Sizing with Heterogeneous Assets," Transportation Science, INFORMS, vol. 39(1), pages 87-103, February.
    6. Salhi, S & Sari, M & Saidi, D & Touati, Nac, 1992. "Adaptation of some vehicle fleet mix heuristics," Omega, Elsevier, vol. 20(5-6), pages 653-660.
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    Cited by:

    1. Hutter, Leonie & Jaehn, Florian & Neumann, Simone, 2019. "Influencing factors on airplane boarding times," Omega, Elsevier, vol. 87(C), pages 177-190.
    2. Sa, Constantijn A.A. & Santos, Bruno F. & Clarke, John-Paul B., 2020. "Portfolio-based airline fleet planning under stochastic demand," Omega, Elsevier, vol. 97(C).

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