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Optimizing for total costs in vehicle routing in urban areas

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  • Ehmke, Jan Fabian
  • Campbell, Ann M.
  • Thomas, Barrett W.

Abstract

Minimizing cost is one of the most important objectives for logistics service providers, and it is not clear how an emphasis on minimizing emissions impacts costs. Most methodologies for routing currently minimize distance or travel time. This paper compares total cost (based on driver and fuel costs), fuel consumption/emissions, distance, and travel time for routes resulting from optimizing each of those measures. We explore the impact of multiple factors on these measures as well as the structure of the routes. Our results suggest that companies need rich cost models and routing algorithms with path flexibility to truly minimize total costs.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:transe:v:116:y:2018:i:c:p:242-265
    DOI: 10.1016/j.tre.2018.06.008
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    References listed on IDEAS

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    5. 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.
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    8. K. Noorliza, 2023. "Determinants of an Environmentally Sustainable Model for Competitiveness," Sustainability, MDPI, vol. 15(2), pages 1-18, January.
    9. Zhaoxia Guo & Stein W. Wallace & Michal Kaut, 2019. "Vehicle Routing with Space- and Time-Correlated Stochastic Travel Times: Evaluating the Objective Function," INFORMS Journal on Computing, INFORMS, vol. 31(4), pages 654-670, October.
    10. Rifki, Omar & Chiabaut, Nicolas & Solnon, Christine, 2020. "On the impact of spatio-temporal granularity of traffic conditions on the quality of pickup and delivery optimal tours," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    11. Sahu, Prasanta K. & Qureshi, Danish & Pani, Agnivesh, 2022. "Examining commercial vehicle fleet ownership decisions and the mediating role of freight generation: A structural equation modeling assessment," Transport Policy, Elsevier, vol. 126(C), pages 26-33.
    12. Sara Ceschia & Luca Di Gaspero & Antonella Meneghetti, 2020. "Extending and Solving the Refrigerated Routing Problem," Energies, MDPI, vol. 13(23), pages 1-24, November.
    13. 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.
    14. Noorliza Karia, 2022. "Antecedents and Consequences of Environmental Capability towards Sustainability and Competitiveness," Sustainability, MDPI, vol. 14(19), pages 1-16, September.
    15. Amiri, Mohsen & Amin, Saman Hassanzadeh & Tavakkoli-Moghaddam, Reza, 2019. "A Lagrangean decomposition approach for a novel two-echelon node-based location-routing problem in an offshore oil and gas supply chain," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 128(C), pages 96-114.
    16. 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.

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