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A speed and departure time optimization algorithm for the pollution-routing problem

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  • Kramer, Raphael
  • Maculan, Nelson
  • Subramanian, Anand
  • Vidal, Thibaut

Abstract

We propose a new speed and departure time optimization algorithm for the pollution-routing problem (PRP), which runs in quadratic time and returns an optimal schedule. This algorithm is embedded into an iterated local search-based metaheuristic to achieve a combined speed, scheduling and routing optimization. The start of the working day is set as a decision variable for individual routes, thus enabling a better assignment of human resources to required demands. Some routes that were evaluated as unprofitable can now appear as viable candidates later in the day, leading to a larger search space and further opportunities of distance optimization via better service consolidation. Extensive computational experiments on available PRP benchmark instances demonstrate the good performance of the algorithm. The flexible departure times from the depot contribute to reduce the operational costs by 8.36% on the considered instances.

Suggested Citation

  • Kramer, Raphael & Maculan, Nelson & Subramanian, Anand & Vidal, Thibaut, 2015. "A speed and departure time optimization algorithm for the pollution-routing problem," European Journal of Operational Research, Elsevier, vol. 247(3), pages 782-787.
    • Handle: RePEc:eee:ejores:v:247:y:2015:i:3:p:782-787
    DOI: 10.1016/j.ejor.2015.06.037
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    References listed on IDEAS

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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. 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.
    3. 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.
    4. Kramer, Raphael & Subramanian, Anand & Vidal, Thibaut & Cabral, Lucídio dos Anjos F., 2015. "A matheuristic approach for the Pollution-Routing Problem," European Journal of Operational Research, Elsevier, vol. 243(2), pages 523-539.
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    Cited by:

    1. 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.
    2. 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).
    3. Ricardo Fukasawa & Qie He & Fernando Santos & Yongjia Song, 2018. "A Joint Vehicle Routing and Speed Optimization Problem," INFORMS Journal on Computing, INFORMS, vol. 30(4), pages 694-709, November.
    4. Qiu, Rui & Xu, Jiuping & Ke, Ruimin & Zeng, Ziqiang & Wang, Yinhai, 2020. "Carbon pricing initiatives-based bi-level pollution routing problem," European Journal of Operational Research, Elsevier, vol. 286(1), pages 203-217.
    5. Emna Marrekchi & Walid Besbes & Diala Dhouib & Emrah Demir, 2021. "A review of recent advances in the operations research literature on the green routing problem and its variants," Annals of Operations Research, Springer, vol. 304(1), pages 529-574, September.
    6. Joanna Szkutnik-Rogoż & Jarosław Ziółkowski & Jerzy Małachowski & Mateusz Oszczypała, 2021. "Mathematical Programming and Solution Approaches for Transportation Optimisation in Supply Network," Energies, MDPI, vol. 14(21), pages 1-32, October.
    7. Judith Mulder & Willem van Jaarsveld & Rommert Dekker, 2019. "Simultaneous Optimization of Speed and Buffer Times with an Application to Liner Shipping," Transportation Science, INFORMS, vol. 53(2), pages 365-382, March.
    8. Xiao, Yiyong & Zuo, Xiaorong & Huang, Jiaoying & Konak, Abdullah & Xu, Yuchun, 2020. "The continuous pollution routing problem," Applied Mathematics and Computation, Elsevier, vol. 387(C).
    9. Anna Franceschetti & Dorothée Honhon & Gilbert Laporte & Tom Van Woensel, 2018. "A Shortest-Path Algorithm for the Departure Time and Speed Optimization Problem," Transportation Science, INFORMS, vol. 52(4), pages 756-768, August.
    10. 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.
    11. Huang, Yixiao & Zhao, Lei & Van Woensel, Tom & Gross, Jean-Philippe, 2017. "Time-dependent vehicle routing problem with path flexibility," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 169-195.
    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. 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.
    14. Raeesi, Ramin & Zografos, Konstantinos G., 2019. "The multi-objective Steiner pollution-routing problem on congested urban road networks," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 457-485.
    15. Yunyun Niu & Zehua Yang & Rong Wen & Jianhua Xiao & Shuai Zhang, 2022. "Solving the Green Open Vehicle Routing Problem Using a Membrane-Inspired Hybrid Algorithm," Sustainability, MDPI, vol. 14(14), pages 1-22, July.
    16. He, Qie & Zhang, Xiaochen & Nip, Kameng, 2017. "Speed optimization over a path with heterogeneous arc costs," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 198-214.
    17. Franceschetti, Anna & Demir, Emrah & Honhon, Dorothée & Van Woensel, Tom & Laporte, Gilbert & Stobbe, Mark, 2017. "A metaheuristic for the time-dependent pollution-routing problem," European Journal of Operational Research, Elsevier, vol. 259(3), pages 972-991.
    18. 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.
    19. Tamás Bányai & Christian Landschützer & Ágota Bányai, 2018. "Markov-Chain Simulation-Based Analysis of Human Resource Structure: How Staff Deployment and Staffing Affect Sustainable Human Resource Strategy," Sustainability, MDPI, vol. 10(10), pages 1-21, October.
    20. Watling, David P. & Connors, Richard D. & Chen, Haibo, 2023. "Fuel-optimal truck path and speed profile in dynamic conditions: An exact algorithm," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1456-1472.
    21. 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.
    22. Behnke, Martin & Kirschstein, Thomas, 2017. "The impact of path selection on GHG emissions in city logistics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 106(C), pages 320-336.

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