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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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    5. 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.
    6. 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.
    7. 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.
    8. 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.
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