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The impact of path selection on GHG emissions in city logistics

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  • Behnke, Martin
  • Kirschstein, Thomas

Abstract

In this paper, we formulate an emission-minimizing vehicle routing problem with heterogeneous vehicles and give rise to the effects of path selection. We take into account different paths for traveling between two locations differing with respect to their emissions. Computational experiments with artificial and real-world data illustrate the effects of path selection by considering networks with different road types like urban roads and highways. The experiments suggest an emission saving potential of about 2–4%. We conclude that in reality a larger emission reduction potential exists when multiple paths are considered in transportation planning.

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  • 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.
  • Handle: RePEc:eee:transe:v:106:y:2017:i:c:p:320-336
    DOI: 10.1016/j.tre.2017.08.011
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    Cited by:

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    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. 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).
    4. Poulad Moradi & Joachim Arts & Josu'e Vel'azquez-Mart'inez, 2023. "Load Asymptotics and Dynamic Speed Optimization for the Greenest Path Problem: A Comprehensive Analysis," Papers 2306.01687, arXiv.org.
    5. Wanjie Hu & Jianjun Dong & Bon-gang Hwang & Rui Ren & Zhilong Chen, 2019. "A Scientometrics Review on City Logistics Literature: Research Trends, Advanced Theory and Practice," Sustainability, MDPI, vol. 11(10), pages 1-27, May.
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    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. Mohammad Zaher Akkad & Tamás Bányai, 2020. "Multi-Objective Approach for Optimization of City Logistics Considering Energy Efficiency," Sustainability, MDPI, vol. 12(18), pages 1-23, September.
    11. Hailin Wu & Fengming Tao & Bo Yang, 2020. "Optimization of Vehicle Routing for Waste Collection and Transportation," IJERPH, MDPI, vol. 17(14), pages 1-26, July.
    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. Letnik, Tomislav & Marksel, Maršenka & Luppino, Giuseppe & Bardi, Andrea & Božičnik, Stane, 2018. "Review of policies and measures for sustainable and energy efficient urban transport," Energy, Elsevier, vol. 163(C), pages 245-257.
    14. Sergio Maria Patella & Gianluca Grazieschi & Valerio Gatta & Edoardo Marcucci & Stefano Carrese, 2020. "The Adoption of Green Vehicles in Last Mile Logistics: A Systematic Review," Sustainability, MDPI, vol. 13(1), pages 1-29, December.
    15. Behnke, Martin & Kirschstein, Thomas & Bierwirth, Christian, 2021. "A column generation approach for an emission-oriented vehicle routing problem on a multigraph," European Journal of Operational Research, Elsevier, vol. 288(3), pages 794-809.
    16. Schmidt, Carise E. & Silva, Arinei C.L. & Darvish, Maryam & Coelho, Leandro C., 2019. "The time-dependent location-routing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 128(C), pages 293-315.
    17. Anna Sciomachen & Maria Truvolo, 2023. "An Exact Approach for Selecting Pickup-Delivery Stations in Urban Areas to Reduce Distribution Emission Costs," Mathematics, MDPI, vol. 11(8), pages 1-18, April.

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