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Urban Freight Truck Routing under Stochastic Congestion and Emission Considerations

Author

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  • Taesung Hwang

    (Asia Pacific School of Logistics and Graduate School of Logistics, Inha University, Incheon 402-751, Korea)

  • Yanfeng Ouyang

    (Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA)

Abstract

Freight trucks are known to be a major source of air pollutants as well as greenhouse gas emissions in U.S. metropolitan areas, and they have significant effects on air quality and global climate change. Emissions from freight trucks during their deliveries should be considered by the trucking service sector when they make routing decisions. This study proposes a model that incorporates total delivery time, various emissions including CO 2 , VOC, NO X , and PM from freight truck activities, and a penalty for late or early arrival into the total cost objective of a stochastic shortest path problem. We focus on urban transportation networks in which random congestion states on each link follows an independent probability distribution. Our model finds the best truck routing on a given network so as to minimize the expected total cost. This problem is formulated into a mathematical model, and two solution algorithms including a dynamic programming approach and a deterministic shortest path heuristic are proposed. Numerical examples show that the proposed approach performs very well even for the large-size U.S. urban networks.

Suggested Citation

  • Taesung Hwang & Yanfeng Ouyang, 2015. "Urban Freight Truck Routing under Stochastic Congestion and Emission Considerations," Sustainability, MDPI, vol. 7(6), pages 1-16, May.
    • Handle: RePEc:gam:jsusta:v:7:y:2015:i:6:p:6610-6625:d:50159
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    References listed on IDEAS

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    Cited by:

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    6. Olapiriyakul, Sun & Nguyen, Thi T., 2019. "Land use and public health impact assessment in a supply chain network design problem: A case study," Journal of Transport Geography, Elsevier, vol. 75(C), pages 70-81.
    7. Jun Du & Bin Jia & Shiteng Zheng, 2022. "Stability Analysis of Continuous Stochastic Linear Model," Sustainability, MDPI, vol. 14(5), pages 1-13, March.
    8. Longlong Leng & Yanwei Zhao & Zheng Wang & Jingling Zhang & Wanliang Wang & Chunmiao Zhang, 2019. "A Novel Hyper-Heuristic for the Biobjective Regional Low-Carbon Location-Routing Problem with Multiple Constraints," Sustainability, MDPI, vol. 11(6), pages 1-31, March.
    9. Sungwon Lee & Taesung Hwang, 2018. "Estimating Emissions from Regional Freight Delivery under Different Urban Development Scenarios," Sustainability, MDPI, vol. 10(4), pages 1-14, April.
    10. Longlong Leng & Yanwei Zhao & Jingling Zhang & Chunmiao Zhang, 2019. "An Effective Approach for the Multiobjective Regional Low-Carbon Location-Routing Problem," IJERPH, MDPI, vol. 16(11), pages 1-28, June.
    11. Francesco Russo & Antonio Comi, 2016. "Urban Freight Transport Planning towards Green Goals: Synthetic Environmental Evidence from Tested Results," Sustainability, MDPI, vol. 8(4), pages 1-18, April.
    12. Magdalena Mucowska, 2021. "Trends of Environmentally Sustainable Solutions of Urban Last-Mile Deliveries on the E-Commerce Market—A Literature Review," Sustainability, MDPI, vol. 13(11), pages 1-26, May.
    13. Vojkan Jovičić & Boštjan Volk & Janko Logar, 2018. "Conditions for the Sustainable Development of Underground Transport in the Ljubljana Basin," Sustainability, MDPI, vol. 10(9), pages 1-23, August.
    14. Jia, Shuwei & Liu, Xiaolu & Yan, Guangle, 2019. "Effect of APCF policy on the haze pollution in China: A system dynamics approach," Energy Policy, Elsevier, vol. 125(C), pages 33-44.
    15. 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.
    16. Taesung Hwang, 2021. "Assignment of Freight Truck Shipment on the U.S. Highway Network," Sustainability, MDPI, vol. 13(11), pages 1-11, June.
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