[go: up one dir, main page]

IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i12p6940-d578495.html
   My bibliography  Save this article

Optimization of Conventional and Green Vehicles Composition under Carbon Emission Cap

Author

Listed:
  • Md. Anisul Islam

    (Department of Mechanical Engineering, Room E2-327, EITC Building, University of Manitoba, Winnipeg, MB R3T 5V6, Canada)

  • Yuvraj Gajpal

    (Department of Supply Chain Management, 631-181 Freedman Crescent, Asper School of Business, University of Manitoba, Winnipeg, MB R3T 5V4, Canada)

Abstract
The CO 2 emission of transportation is significantly reduced by the employment of green vehicles to the existing vehicle fleet of the organizations. This paper intends to optimize the composition of conventional and green vehicles for a logistics distribution problem operating under a carbon emission cap imposed by the government. The underlying problem involves product delivery by the vehicles starting from a single depot to geographically distributed customers. The delivery occurs within specified time windows. To solve the proposed problem, we design a hybrid metaheuristic solution based on ant colony optimization (ACO) and variable neighborhood search (VNS) algorithms. Extensive computational experiments have been performed on newly generated problem instances and benchmark problem instances adopted from the literature. The proposed hybrid ACO is proven to be superior to the state-of-the-art algorithms available in the literature. We obtain 21 new best-known solutions out of 56 benchmark instances of vehicle routing problem with time windows (VRPTW). The proposed mixed fleet model obtains the best composition of conventional and green vehicles with a 6.90% reduced amount of CO 2 emissions compared to the case when the fleet consists of conventional vehicles only.

Suggested Citation

  • Md. Anisul Islam & Yuvraj Gajpal, 2021. "Optimization of Conventional and Green Vehicles Composition under Carbon Emission Cap," Sustainability, MDPI, vol. 13(12), pages 1-20, June.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:12:p:6940-:d:578495
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/12/6940/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/13/12/6940/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Qureshi, A.G. & Taniguchi, E. & Yamada, T., 2009. "An exact solution approach for vehicle routing and scheduling problems with soft time windows," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 45(6), pages 960-977, November.
    2. Song, Shuang & Govindan, Kannan & Xu, Lei & Du, Peng & Qiao, Xiaojiao, 2017. "Capacity and production planning with carbon emission constraints," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 97(C), pages 132-150.
    3. Shaojian Qu & Hui Yang & Ying Ji, 2021. "Low-carbon supply chain optimization considering warranty period and carbon emission reduction level under cap-and-trade regulation," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(12), pages 18040-18067, December.
    4. Humberto Brandão de Oliveira & Germano Vasconcelos, 2010. "A hybrid search method for the vehicle routing problem with time windows," Annals of Operations Research, Springer, vol. 180(1), pages 125-144, November.
    5. Heinold, Arne & Meisel, Frank, 2020. "Emission limits and emission allocation schemes in intermodal freight transportation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    6. Bektas, Tolga & Laporte, Gilbert, 2011. "The Pollution-Routing Problem," Transportation Research Part B: Methodological, Elsevier, vol. 45(8), pages 1232-1250, September.
    7. Sanjay Jharkharia & Chiranjit Das, 2019. "Vehicle routing analyses with integrated order picking and delivery problem under carbon cap and trade policy," Management Research Review, Emerald Group Publishing Limited, vol. 43(2), pages 223-243, September.
    8. Bhusiri, Narath & Qureshi, Ali Gul & Taniguchi, Eiichi, 2014. "The trade-off between fixed vehicle costs and time-dependent arrival penalties in a routing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 62(C), pages 1-22.
    9. Matteo Salani & Maria Battarra & Luca Maria Gambardella, 2016. "Exact Algorithms for the Vehicle Routing Problem with Soft Time Windows," Operations Research Proceedings, in: Marco Lübbecke & Arie Koster & Peter Letmathe & Reinhard Madlener & Britta Peis & Grit Walther (ed.), Operations Research Proceedings 2014, edition 1, pages 481-486, Springer.
    10. Demir, Emrah & Bektaş, Tolga & Laporte, Gilbert, 2014. "The bi-objective Pollution-Routing Problem," European Journal of Operational Research, Elsevier, vol. 232(3), pages 464-478.
    11. B Yu & Z-Z Yang & J-X Xie, 2011. "A parallel improved ant colony optimization for multi-depot vehicle routing problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(1), pages 183-188, January.
    12. Cheng, Chun & Qi, Mingyao & Wang, Xingyi & Zhang, Ying, 2016. "Multi-period inventory routing problem under carbon emission regulations," International Journal of Production Economics, Elsevier, vol. 182(C), pages 263-275.
    13. 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.
    14. Qiu, Yuzhuo & Qiao, Jun & Pardalos, Panos M., 2017. "A branch-and-price algorithm for production routing problems with carbon cap-and-trade," Omega, Elsevier, vol. 68(C), pages 49-61.
    15. Olli Bräysy & Michel Gendreau, 2005. "Vehicle Routing Problem with Time Windows, Part I: Route Construction and Local Search Algorithms," Transportation Science, INFORMS, vol. 39(1), pages 104-118, February.
    16. W-C Chiang & R A Russell, 2004. "A metaheuristic for the vehicle-routeing problem with soft time windows," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(12), pages 1298-1310, December.
    17. Guan, Jian & Lin, Geng, 2016. "Hybridizing variable neighborhood search with ant colony optimization for solving the single row facility layout problem," European Journal of Operational Research, Elsevier, vol. 248(3), pages 899-909.
    18. Lixia Li & Yu Yang & Gaoyuan Qin, 2019. "Optimization of Integrated Inventory Routing Problem for Cold Chain Logistics Considering Carbon Footprint and Carbon Regulations," Sustainability, MDPI, vol. 11(17), pages 1-22, August.
    19. Z Fu & R Eglese & L Y O Li, 2008. "A unified tabu search algorithm for vehicle routing problems with soft time windows," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(5), pages 663-673, May.
    20. Gajpal, Yuvraj & Abad, P.L., 2009. "Multi-ant colony system (MACS) for a vehicle routing problem with backhauls," European Journal of Operational Research, Elsevier, vol. 196(1), pages 102-117, July.
    21. Olli Bräysy & Michel Gendreau, 2005. "Vehicle Routing Problem with Time Windows, Part II: Metaheuristics," Transportation Science, INFORMS, vol. 39(1), pages 119-139, February.
    22. Hideki Hashimoto & Mutsunori Yagiura & Shinji Imahori & Toshihide Ibaraki, 2013. "Recent progress of local search in handling the time window constraints of the vehicle routing problem," Annals of Operations Research, Springer, vol. 204(1), pages 171-187, April.
    23. Gmira, Maha & Gendreau, Michel & Lodi, Andrea & Potvin, Jean-Yves, 2021. "Tabu search for the time-dependent vehicle routing problem with time windows on a road network," European Journal of Operational Research, Elsevier, vol. 288(1), pages 129-140.
    24. Marinakis, Yannis & Migdalas, Athanasios & Sifaleras, Angelo, 2017. "A hybrid Particle Swarm Optimization – Variable Neighborhood Search algorithm for Constrained Shortest Path problems," European Journal of Operational Research, Elsevier, vol. 261(3), pages 819-834.
    25. Marius M. Solomon, 1987. "Algorithms for the Vehicle Routing and Scheduling Problems with Time Window Constraints," Operations Research, INFORMS, vol. 35(2), pages 254-265, April.
    26. Baldacci, Roberto & Mingozzi, Aristide & Roberti, Roberto, 2012. "Recent exact algorithms for solving the vehicle routing problem under capacity and time window constraints," European Journal of Operational Research, Elsevier, vol. 218(1), pages 1-6.
    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. Qi Yao & Shenjun Zhu & Yanhui Li, 2022. "Green Vehicle-Routing Problem of Fresh Agricultural Products Considering Carbon Emission," IJERPH, MDPI, vol. 19(14), pages 1-17, July.
    2. Xiaohong Yin & Yufei Wu & Qiang Liu, 2023. "Dynamic Evaluation of Energy Carbon Efficiency in the Logistics Industry Based on Catastrophe Progression," Sustainability, MDPI, vol. 15(6), pages 1-17, March.
    3. Garside, Annisa Kesy & Ahmad, Robiah & Muhtazaruddin, Mohd Nabil Bin, 2024. "A recent review of solution approaches for green vehicle routing problem and its variants," Operations Research Perspectives, Elsevier, vol. 12(C).

    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. Bhusiri, Narath & Qureshi, Ali Gul & Taniguchi, Eiichi, 2014. "The trade-off between fixed vehicle costs and time-dependent arrival penalties in a routing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 62(C), pages 1-22.
    3. Nicolas Rincon-Garcia & Ben J. Waterson & Tom J. Cherrett, 2018. "Requirements from vehicle routing software: perspectives from literature, developers and the freight industry," Transport Reviews, Taylor & Francis Journals, vol. 38(1), pages 117-138, January.
    4. 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).
    5. Matteo Salani & Maria Battarra, 2018. "The opportunity cost of time window violations," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 7(4), pages 343-361, December.
    6. Xiao, Yiyong & Konak, Abdullah, 2016. "The heterogeneous green vehicle routing and scheduling problem with time-varying traffic congestion," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 88(C), pages 146-166.
    7. Vidal, Thibaut & Crainic, Teodor Gabriel & Gendreau, Michel & Prins, Christian, 2013. "Heuristics for multi-attribute vehicle routing problems: A survey and synthesis," European Journal of Operational Research, Elsevier, vol. 231(1), pages 1-21.
    8. Hideki Hashimoto & Mutsunori Yagiura & Shinji Imahori & Toshihide Ibaraki, 2013. "Recent progress of local search in handling the time window constraints of the vehicle routing problem," Annals of Operations Research, Springer, vol. 204(1), pages 171-187, April.
    9. Shijin Wang & Xiaodong Wang & Xin Liu & Jianbo Yu, 2018. "A Bi-Objective Vehicle-Routing Problem with Soft Time Windows and Multiple Depots to Minimize the Total Energy Consumption and Customer Dissatisfaction," Sustainability, MDPI, vol. 10(11), pages 1-21, November.
    10. Ehmke, Jan Fabian & Campbell, Ann Melissa & Urban, Timothy L., 2015. "Ensuring service levels in routing problems with time windows and stochastic travel times," European Journal of Operational Research, Elsevier, vol. 240(2), pages 539-550.
    11. 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.
    12. Ehmke, Jan Fabian & Campbell, Ann M. & Thomas, Barrett W., 2018. "Optimizing for total costs in vehicle routing in urban areas," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 116(C), pages 242-265.
    13. 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.
    14. Maria João Santos & Pedro Amorim & Alexandra Marques & Ana Carvalho & Ana Póvoa, 2020. "The vehicle routing problem with backhauls towards a sustainability perspective: a review," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(2), pages 358-401, July.
    15. Ehmke, Jan Fabian & Campbell, Ann Melissa, 2014. "Customer acceptance mechanisms for home deliveries in metropolitan areas," European Journal of Operational Research, Elsevier, vol. 233(1), pages 193-207.
    16. Zajac, Sandra & Huber, Sandra, 2021. "Objectives and methods in multi-objective routing problems: a survey and classification scheme," European Journal of Operational Research, Elsevier, vol. 290(1), pages 1-25.
    17. Schyns, M., 2015. "An ant colony system for responsive dynamic vehicle routing," European Journal of Operational Research, Elsevier, vol. 245(3), pages 704-718.
    18. Andres Figliozzi, Miguel, 2012. "The time dependent vehicle routing problem with time windows: Benchmark problems, an efficient solution algorithm, and solution characteristics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(3), pages 616-636.
    19. Schneider, Michael & Schwahn, Fabian & Vigo, Daniele, 2017. "Designing granular solution methods for routing problems with time windows," European Journal of Operational Research, Elsevier, vol. 263(2), pages 493-509.
    20. 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.

    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:6940-:d:578495. 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.