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Mixed fleet scheduling method for airport ground service vehicles under the trend of electrification

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  • Bao, Dan-Wen
  • Zhou, Jia-Yi
  • Zhang, Zi-Qian
  • Chen, Zhuo
  • Kang, Di

Abstract

Electric ground support equipment (GSE) has been promoted by airports to reduce carbon emissions, and most airports operate both fuel and electric vehicles. In order to fill the gap in the research of GSE scheduling problem with mixed fleet of fuel vehicles and electric vehicles, this paper establishes a mixed operation model of fuel and electric vehicles with time window with the objective function of minimizing the sum of time cost, energy cost and emission cost, and considers the energy consumption of a new type of electric aircraft towing tractor which have APU substitution function. Then solve it by using a reliable adaptive large neighborhood search algorithm, which improves the quality of the solution through the simulated annealing principle and expansion of the applicability of the adaptive mechanism. Furthermore, 2 scenarios with different characteristics of road network scale, the terminal configuration and flight were constructed on the basis of Nanjing Lukou international airport data, and each scenario have 5 different proportions of fleets in order to reflect the operation characteristics along with the change of electric vehicles proportion. The results show that: (1) Scenario characteristics will affect the optimal fleet allocation strategy; (2) Compared with large airports, small airports have higher emission reduction efficiency and lower energy saving efficiency; (3) Airport ground electrification increases flight delays, especially at smaller airports with a more inflexible network. This study can provide data reference for the optimal fleet configuration in airports with mixed operation with fuel and electric vehicles.

Suggested Citation

  • Bao, Dan-Wen & Zhou, Jia-Yi & Zhang, Zi-Qian & Chen, Zhuo & Kang, Di, 2023. "Mixed fleet scheduling method for airport ground service vehicles under the trend of electrification," Journal of Air Transport Management, Elsevier, vol. 108(C).
  • Handle: RePEc:eee:jaitra:v:108:y:2023:i:c:s0969699723000224
    DOI: 10.1016/j.jairtraman.2023.102379
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    1. Bektas, Tolga & Laporte, Gilbert, 2011. "The Pollution-Routing Problem," Transportation Research Part B: Methodological, Elsevier, vol. 45(8), pages 1232-1250, September.
    2. Ropke, Stefan & Pisinger, David, 2006. "A unified heuristic for a large class of Vehicle Routing Problems with Backhauls," European Journal of Operational Research, Elsevier, vol. 171(3), pages 750-775, June.
    3. 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.
    4. Li, Lu & Lo, Hong K. & Huang, Wei & Xiao, Feng, 2021. "Mixed bus fleet location-routing-scheduling under range uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 146(C), pages 155-179.
    5. Fukasawa, Ricardo & He, Qie & Song, Yongjia, 2016. "A disjunctive convex programming approach to the pollution-routing problem," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 61-79.
    6. Koç, Çağrı & Bektaş, Tolga & Jabali, Ola & Laporte, Gilbert, 2014. "The fleet size and mix pollution-routing problem," Transportation Research Part B: Methodological, Elsevier, vol. 70(C), pages 239-254.
    7. Alinaghian, Mahdi & Shokouhi, Nadia, 2018. "Multi-depot multi-compartment vehicle routing problem, solved by a hybrid adaptive large neighborhood search," Omega, Elsevier, vol. 76(C), pages 85-99.
    8. Goeke, D. & Schneider, M., 2015. "Routing a Mixed Fleet of Electric and Conventional Vehicles," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 65939, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    9. Lu, Chung-Cheng & Diabat, Ali & Li, Yi-Ting & Yang, Yu-Min, 2022. "Combined passenger and parcel transportation using a mixed fleet of electric and gasoline vehicles," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    10. A Norin & D Yuan & T A Granberg & P V&aauml;rbrand, 2012. "Scheduling de-icing vehicles within airport logistics: a heuristic algorithm and performance evaluation," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 63(8), pages 1116-1125, August.
    11. Demir, Emrah & Bektaş, Tolga & Laporte, Gilbert, 2012. "An adaptive large neighborhood search heuristic for the Pollution-Routing Problem," European Journal of Operational Research, Elsevier, vol. 223(2), pages 346-359.
    12. Goeke, Dominik & Schneider, Michael, 2015. "Routing a mixed fleet of electric and conventional vehicles," European Journal of Operational Research, Elsevier, vol. 245(1), pages 81-99.
    13. Hiermann, Gerhard & Hartl, Richard F. & Puchinger, Jakob & Vidal, Thibaut, 2019. "Routing a mix of conventional, plug-in hybrid, and electric vehicles," European Journal of Operational Research, Elsevier, vol. 272(1), pages 235-248.
    14. Dayarian, Iman & Crainic, Teodor Gabriel & Gendreau, Michel & Rei, Walter, 2016. "An adaptive large-neighborhood search heuristic for a multi-period vehicle routing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 95(C), pages 95-123.
    15. Suzuki, Yoshinori, 2016. "A dual-objective metaheuristic approach to solve practical pollution routing problem," International Journal of Production Economics, Elsevier, vol. 176(C), pages 143-153.
    16. Sun, Peng & Veelenturf, Lucas P. & Hewitt, Mike & Van Woensel, Tom, 2020. "Adaptive large neighborhood search for the time-dependent profitable pickup and delivery problem with time windows," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 138(C).
    17. Onur Can Saka & Sinan Gürel & Tom Van Woensel, 2017. "Using cost change estimates in a local search heuristic for the pollution routing problem," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(2), pages 557-587, March.
    18. Macrina, Giusy & Laporte, Gilbert & Guerriero, Francesca & Di Puglia Pugliese, Luigi, 2019. "An energy-efficient green-vehicle routing problem with mixed vehicle fleet, partial battery recharging and time windows," European Journal of Operational Research, Elsevier, vol. 276(3), pages 971-982.
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