IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i12p6703-d574115.html
   My bibliography  Save this article

Dynamic Inventory Routing and Pricing Problem with a Mixed Fleet of Electric and Conventional Urban Freight Vehicles

Author

Listed:
  • Hamid R. Sayarshad

    (Robert A. Foisie School of Business, Worcester Polytechnic Institute, Worcester, MA 01609, USA
    Department of Research and Development, Optywar Company, Irvine, CA 92612, USA)

  • Vahid Mahmoodian

    (Industrial & Management Systems Engineering, University of South Florida, Tampa, FL 33620, USA)

  • Nebojša Bojović

    (Faculty of Transport and Traffic Engineering, University of Belgrade, Vojvode Stepe 305, 11000 Belgrade, Serbia)

Abstract

Urban freight transport is essential for supporting our society regarding providing the daily needs of consumers and local businesses. In addition, it allows for the movement of goods, is distributed within urban environments, provides thousands of jobs, and supports economic growth. However, a number of issues are associated with urban freight transport, including environmental impacts, road congestion, and land use of freight facilities that conflicts with residential land use. Electric freight vehicles create zero emissions and provide a sustainable delivery system in comparison with conventional freight vehicles. In this study, a novel dynamic inventory routing and pricing problem under a mixed fleet of electric and conventional vehicles was formulated to minimize the total travel and charging costs. The proposed model is capable of deciding on replenishment times and amounts and vehicle routes. We aimed to determine the maximum social welfare (SW) capable of providing an optimal trade-off between the supplier cost and customer delay that uses a mixed fleet of vehicles. Our computational study was conducted on real data generated from a delivery dataset in Tehran. Under the proposed policy with a fleet of only electric vehicles, the SW increased by 3% while the average customer delay reduced by 15% compared with a fleet of conventional vehicles. The results show that the number of served customers and customer delay would be affected by transitioning conventional urban freight vehicles to electric vehicles. Therefore, the proposed delivery system has a significant impact on energy savings and emissions.

Suggested Citation

  • Hamid R. Sayarshad & Vahid Mahmoodian & Nebojša Bojović, 2021. "Dynamic Inventory Routing and Pricing Problem with a Mixed Fleet of Electric and Conventional Urban Freight Vehicles," Sustainability, MDPI, vol. 13(12), pages 1-16, June.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:12:p:6703-:d:574115
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/12/6703/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/13/12/6703/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Majid Salavati-Khoshghalb & Michel Gendreau & Ola Jabali & Walter Rei, 2019. "A hybrid recourse policy for the vehicle routing problem with stochastic demands," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 8(3), pages 269-298, September.
    2. Khayyam Masood & Matteo Zoppi & Vincent Fremont & Rezia M. Molfino, 2021. "From Drive-By-Wire to Autonomous Vehicle: Urban Freight Vehicle Perspectives," Sustainability, MDPI, vol. 13(3), pages 1-21, January.
    3. Majid Salavati-Khoshghalb & Michel Gendreau & Ola Jabali & Walter Rei, 2019. "A Rule-Based Recourse for the Vehicle Routing Problem with Stochastic Demands," Transportation Science, INFORMS, vol. 53(5), pages 1334-1353, September.
    4. Franceschetti, Anna & Honhon, Dorothée & Van Woensel, Tom & Bektaş, Tolga & Laporte, Gilbert, 2013. "The time-dependent pollution-routing problem," Transportation Research Part B: Methodological, Elsevier, vol. 56(C), pages 265-293.
    5. Schiffer, Maximilian & Walther, Grit, 2017. "The electric location routing problem with time windows and partial recharging," European Journal of Operational Research, Elsevier, vol. 260(3), pages 995-1013.
    6. Schiffer, Maximilian & Walther, Grit, 2018. "Strategic planning of electric logistics fleet networks: A robust location-routing approach," Omega, Elsevier, vol. 80(C), pages 31-42.
    7. Pelletier, Samuel & Jabali, Ola & Laporte, Gilbert, 2019. "The electric vehicle routing problem with energy consumption uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 126(C), pages 225-255.
    8. Barth, Matthew & Younglove, Theodore & Scora, George, 2005. "Development of a Heavy-Duty Diesel Modal Emissions and Fuel Consumption Model," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt67f0v3zf, Institute of Transportation Studies, UC Berkeley.
    9. 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.
    10. Felipe, Ángel & Ortuño, M. Teresa & Righini, Giovanni & Tirado, Gregorio, 2014. "A heuristic approach for the green vehicle routing problem with multiple technologies and partial recharges," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 71(C), pages 111-128.
    11. 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).
    12. Sayarshad, Hamid R. & Sattar, Shahram & Oliver Gao, H., 2020. "A scalable non-myopic atomic game for a smart parking mechanism," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 140(C).
    13. Wang, Minxi & Wang, Yajie & Liu, Wei & Ma, Yu & Xiang, Longtao & Yang, Yunqi & Li, Xin, 2021. "How to achieve a win–win scenario between cost and customer satisfaction for cold chain logistics?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    14. Xuanjing Fang & Yanan Du & Yuzhuo Qiu, 2017. "Reducing Carbon Emissions in a Closed-Loop Production Routing Problem with Simultaneous Pickups and Deliveries under Carbon Cap-and-Trade," Sustainability, MDPI, vol. 9(12), pages 1-15, November.
    15. Henning Preis & Stefan Frank & Karl Nachtigall, 2014. "Energy-Optimized Routing of Electric Vehicles in Urban Delivery Systems," Operations Research Proceedings, in: Stefan Helber & Michael Breitner & Daniel Rösch & Cornelia Schön & Johann-Matthias Graf von der Schu (ed.), Operations Research Proceedings 2012, edition 127, pages 583-588, Springer.
    16. Barth, Matthew & Boriboonsomsin, Kanok, 2008. "Real-World CO2 Impacts of Traffic Congestion," University of California Transportation Center, Working Papers qt4fx9g4gn, University of California Transportation Center.
    17. Murakami, Keisuke, 2017. "A new model and approach to electric and diesel-powered vehicle routing," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 107(C), pages 23-37.
    18. Adler, Jonathan D. & Mirchandani, Pitu B., 2014. "Online routing and battery reservations for electric vehicles with swappable batteries," Transportation Research Part B: Methodological, Elsevier, vol. 70(C), pages 285-302.
    19. Hiermann, Gerhard & Puchinger, Jakob & Ropke, Stefan & Hartl, Richard F., 2016. "The Electric Fleet Size and Mix Vehicle Routing Problem with Time Windows and Recharging Stations," European Journal of Operational Research, Elsevier, vol. 252(3), pages 995-1018.
    20. Montoya, Alejandro & Guéret, Christelle & Mendoza, Jorge E. & Villegas, Juan G., 2017. "The electric vehicle routing problem with nonlinear charging function," Transportation Research Part B: Methodological, Elsevier, vol. 103(C), pages 87-110.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Surya Michrandi Nasution & Emir Husni & Kuspriyanto Kuspriyanto & Rahadian Yusuf, 2022. "Personalized Route Recommendation Using F-AHP-Express," Sustainability, MDPI, vol. 14(17), pages 1-28, August.
    2. Surya Michrandi Nasution & Emir Husni & Kuspriyanto Kuspriyanto & Rahadian Yusuf & Bernardo Nugroho Yahya, 2021. "Contextual Route Recommendation System in Heterogeneous Traffic Flow," Sustainability, MDPI, vol. 13(23), pages 1-21, November.

    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. 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).
    2. Mohammad Asghari & Seyed Mohammad Javad Mirzapour Al-E-Hashem, 2021. "Green vehicle routing problem: A state-of-the-art review," Post-Print hal-03182944, HAL.
    3. 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.
    4. Pelletier, Samuel & Jabali, Ola & Laporte, Gilbert, 2019. "The electric vehicle routing problem with energy consumption uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 126(C), pages 225-255.
    5. Pelletier, Samuel & Jabali, Ola & Laporte, Gilbert, 2018. "Charge scheduling for electric freight vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 115(C), pages 246-269.
    6. 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.
    7. 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.
    8. Raeesi, Ramin & Zografos, Konstantinos G., 2022. "Coordinated routing of electric commercial vehicles with intra-route recharging and en-route battery swapping," European Journal of Operational Research, Elsevier, vol. 301(1), pages 82-109.
    9. Azra Ghobadi & Mohammad Fallah & Reza Tavakkoli-Moghaddam & Hamed Kazemipoor, 2022. "A Fuzzy Two-Echelon Model to Optimize Energy Consumption in an Urban Logistics Network with Electric Vehicles," Sustainability, MDPI, vol. 14(21), pages 1-31, October.
    10. Masmoudi, Mohamed Amine & Hosny, Manar & Demir, Emrah & Genikomsakis, Konstantinos N. & Cheikhrouhou, Naoufel, 2018. "The dial-a-ride problem with electric vehicles and battery swapping stations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 392-420.
    11. Xiao, Yiyong & Zhang, Yue & Kaku, Ikou & Kang, Rui & Pan, Xing, 2021. "Electric vehicle routing problem: A systematic review and a new comprehensive model with nonlinear energy recharging and consumption," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    12. 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.
    13. 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.
    14. Bektaş, Tolga & Ehmke, Jan Fabian & Psaraftis, Harilaos N. & Puchinger, Jakob, 2019. "The role of operational research in green freight transportation," European Journal of Operational Research, Elsevier, vol. 274(3), pages 807-823.
    15. 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.
    16. Cortés-Murcia, David L. & Prodhon, Caroline & Murat Afsar, H., 2019. "The electric vehicle routing problem with time windows, partial recharges and satellite customers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 130(C), pages 184-206.
    17. 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.
    18. 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.
    19. LIAN, Ying & LUCAS, Flavien & SÖRENSEN, Kenneth, 2022. "The electric on-demand bus routing problem with partial charging and nonlinear functions," Working Papers 2022005, University of Antwerp, Faculty of Business and Economics.
    20. 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).

    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:gam:jsusta:v:13:y:2021:i:12:p:6703-:d:574115. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.