IDEAS home Printed from https://ideas.repec.org/p/cdl/itsdav/qt0nj024qn.html
   My bibliography  Save this paper

Routing Strategies for Efficient Deployment of Alternative Fuel Vehicles for Freight Delivery

Author

Listed:
  • Dessouky, Maged M
  • Shao, Yihuan E

Abstract

With increasing concerns on environmental issues, recent research on Vehicle Routing Problems (VRP) has added new factors such as greenhouse gas emissions and alternative fuel vehicles into the models. In this report, the authors consider one such promising alternative fuel vehicle, Compressed Natural Gas (CNG). However, due to the limited number of available fueling stations and small fuel tank capacity, CNG trucks face several challenges on their way to replacing traditional diesel trucks. Even though CNG trucks have advantages on less greenhouse gas emissions and cheaper fuel cost, the detours to the fueling station may increase the total travel distance. The authors introduce the CNG Truck Routing Problem with Fueling Stations (CTRPFS) to model decisions to be made with regards to the vehicle routes including the choice of fueling stations. Moreover the authors consider load capacity, fuel tank capacity and the driver’s daily traveling distance limitation. The authors develop a Mixed Integer Programming (MIP) model with preprocessing and valid inequalities to solve the problem optimally. A hybrid heuristic method is also proposed to solve this problem, which combines an Adaptive Large Neighborhood Search (ALNS) with a local search and a MIP model. View the NCST Project Webpage

Suggested Citation

  • Dessouky, Maged M & Shao, Yihuan E, 2017. "Routing Strategies for Efficient Deployment of Alternative Fuel Vehicles for Freight Delivery," Institute of Transportation Studies, Working Paper Series qt0nj024qn, Institute of Transportation Studies, UC Davis.
    • Handle: RePEc:cdl:itsdav:qt0nj024qn
    as

    Download full text from publisher

    File URL: https://www.escholarship.org/uc/item/0nj024qn.pdf;origin=repeccitec
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Demir, Emrah & Bektaş, Tolga & Laporte, Gilbert, 2014. "A review of recent research on green road freight transportation," European Journal of Operational Research, Elsevier, vol. 237(3), pages 775-793.
    2. J-F Chen & T-H Wu, 2006. "Vehicle routing problem with simultaneous deliveries and pickups," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(5), pages 579-587, May.
    3. Michael Schneider & Andreas Stenger & Dominik Goeke, 2014. "The Electric Vehicle-Routing Problem with Time Windows and Recharging Stations," Transportation Science, INFORMS, vol. 48(4), pages 500-520, November.
    4. Schneider, M. & Stenger, A. & Goeke, D., 2014. "The Electric Vehicle Routing Problem with Time Windows and Recharging Stations," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 62382, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    5. Laporte, Gilbert, 1992. "The vehicle routing problem: An overview of exact and approximate algorithms," European Journal of Operational Research, Elsevier, vol. 59(3), pages 345-358, June.
    6. Stefan Ropke & David Pisinger, 2006. "An Adaptive Large Neighborhood Search Heuristic for the Pickup and Delivery Problem with Time Windows," Transportation Science, INFORMS, vol. 40(4), pages 455-472, November.
    7. G. B. Dantzig & J. H. Ramser, 1959. "The Truck Dispatching Problem," Management Science, INFORMS, vol. 6(1), pages 80-91, October.
    8. Khan, Muhammad Imran & Yasmin, Tabassum & Shakoor, Abdul, 2015. "Technical overview of compressed natural gas (CNG) as a transportation fuel," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 785-797.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Baals, Julian & Emde, Simon & Turkensteen, Marcel, 2023. "Minimizing earliness-tardiness costs in supplier networks—A just-in-time truck routing problem," European Journal of Operational Research, Elsevier, vol. 306(2), pages 707-741.
    2. Imen Ben Mohamed & Walid Klibi & Olivier Labarthe & Jean-Christophe Deschamps & Mohamed Zied Babai, 2017. "Modelling and solution approaches for the interconnected city logistics," International Journal of Production Research, Taylor & Francis Journals, vol. 55(9), pages 2664-2684, May.
    3. 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.
    4. Wu, Guoyuan & Peng, Dongbo & Boriboonsomsin, Kanok, 2024. "Developing an Efficient Dispatching Strategy to Support Commercial Fleet Electrification," Institute of Transportation Studies, Working Paper Series qt2qz0n2gv, Institute of Transportation Studies, UC Davis.
    5. 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).
    6. Zhang, Shuai & Gajpal, Yuvraj & Appadoo, S.S. & Abdulkader, M.M.S., 2018. "Electric vehicle routing problem with recharging stations for minimizing energy consumption," International Journal of Production Economics, Elsevier, vol. 203(C), pages 404-413.
    7. Herbert Kopfer & Benedikt Vornhusen, 2019. "Energy vehicle routing problem for differently sized and powered vehicles," Journal of Business Economics, Springer, vol. 89(7), pages 793-821, September.
    8. Goeke, Dominik, 2019. "Granular tabu search for the pickup and delivery problem with time windows and electric vehicles," European Journal of Operational Research, Elsevier, vol. 278(3), pages 821-836.
    9. Raeesi, Ramin & Zografos, Konstantinos G., 2020. "The electric vehicle routing problem with time windows and synchronised mobile battery swapping," Transportation Research Part B: Methodological, Elsevier, vol. 140(C), pages 101-129.
    10. Singh, Nitish & Dang, Quang-Vinh & Akcay, Alp & Adan, Ivo & Martagan, Tugce, 2022. "A matheuristic for AGV scheduling with battery constraints," European Journal of Operational Research, Elsevier, vol. 298(3), pages 855-873.
    11. 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).
    12. Zu-Jun Ma & Fei Yang & Ying Dai & Zuo-Jun Max Shen, 2021. "The Migratory Beekeeping Routing Problem: Model and an Exact Algorithm," INFORMS Journal on Computing, INFORMS, vol. 33(1), pages 319-335, January.
    13. Cui, Shaohua & Ma, Xiaolei & Zhang, Mingheng & Yu, Bin & Yao, Baozhen, 2022. "The parallel mobile charging service for free-floating shared electric vehicle clusters," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 160(C).
    14. Samuel Pelletier & Ola Jabali & Gilbert Laporte, 2016. "50th Anniversary Invited Article—Goods Distribution with Electric Vehicles: Review and Research Perspectives," Transportation Science, INFORMS, vol. 50(1), pages 3-22, February.
    15. Hui Li & Jian Zhou & Kexin Xu, 2023. "Evolution of Green Vehicle Routing Problem: A Bibliometric and Visualized Review," Sustainability, MDPI, vol. 15(23), pages 1-27, November.
    16. Dönmez, Sercan & Koç, Çağrı & Altıparmak, Fulya, 2022. "The mixed fleet vehicle routing problem with partial recharging by multiple chargers: Mathematical model and adaptive large neighborhood search," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 167(C).
    17. Joonyup Eun & Byung Duk Song & Sangbok Lee & Dae-Eun Lim, 2019. "Mathematical Investigation on the Sustainability of UAV Logistics," Sustainability, MDPI, vol. 11(21), pages 1-15, October.
    18. Sistig, Hubert Maximilian & Sauer, Dirk Uwe, 2023. "Metaheuristic for the integrated electric vehicle and crew scheduling problem," Applied Energy, Elsevier, vol. 339(C).
    19. Yang, Tiannuo & Chu, Zhongzhu & Wang, Bailin, 2023. "Feasibility on the integration of passenger and freight transportation in rural areas: A service mode and an optimization model," Socio-Economic Planning Sciences, Elsevier, vol. 88(C).
    20. Sam Heshmati & Jannes Verstichel & Eline Esprit & Greet Vanden Berghe, 2019. "Alternative e-commerce delivery policies," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 8(3), pages 217-248, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cdl:itsdav:qt0nj024qn. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Lisa Schiff (email available below). General contact details of provider: https://edirc.repec.org/data/itucdus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.