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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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    1. Ehmke, Jan Fabian & Campbell, Ann Melissa & Thomas, Barrett W., 2016. "Vehicle routing to minimize time-dependent emissions in urban areas," European Journal of Operational Research, Elsevier, vol. 251(2), pages 478-494.
    2. Tolga Bektaş & Emrah Demir & Gilbert Laporte, 2016. "Green Vehicle Routing," International Series in Operations Research & Management Science, in: Harilaos N. Psaraftis (ed.), Green Transportation Logistics, edition 127, chapter 0, pages 243-265, Springer.
    3. Bektas, Tolga & Laporte, Gilbert, 2011. "The Pollution-Routing Problem," Transportation Research Part B: Methodological, Elsevier, vol. 45(8), pages 1232-1250, September.
    4. 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.
    5. Irnich, S. & Schneider, M. & Vigo, D., 2014. "Four Variants of the Vehicle Routing Problem," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 63514, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    6. Koç, Çağrı & Bektaş, Tolga & Jabali, Ola & Laporte, Gilbert, 2014. "The fleet size and mix pollution-routing problem," Transportation Research Part B: Methodological, Elsevier, vol. 70(C), pages 239-254.
    7. Bernhard Fleischmann & Martin Gietz & Stefan Gnutzmann, 2004. "Time-Varying Travel Times in Vehicle Routing," Transportation Science, INFORMS, vol. 38(2), pages 160-173, May.
    8. 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.
    9. Fu, Liping & Rilett, L. R., 1998. "Expected shortest paths in dynamic and stochastic traffic networks," Transportation Research Part B: Methodological, Elsevier, vol. 32(7), pages 499-516, September.
    10. Zachariadis, Emmanouil E. & Tarantilis, Christos D. & Kiranoudis, Chris T., 2015. "The load-dependent vehicle routing problem and its pick-up and delivery extension," Transportation Research Part B: Methodological, Elsevier, vol. 71(C), pages 158-181.
    11. Demir, Emrah & Bektaş, Tolga & Laporte, Gilbert, 2014. "A review of recent research on green road freight transportation," European Journal of Operational Research, Elsevier, vol. 237(3), pages 775-793.
    12. 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.
    13. Qian, Jiani & Eglese, Richard, 2016. "Fuel emissions optimization in vehicle routing problems with time-varying speeds," European Journal of Operational Research, Elsevier, vol. 248(3), pages 840-848.
    14. Wen, Liang & Çatay, Bülent & Eglese, Richard, 2014. "Finding a minimum cost path between a pair of nodes in a time-varying road network with a congestion charge," European Journal of Operational Research, Elsevier, vol. 236(3), pages 915-923.
    15. 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.
    16. Marius M. Solomon, 1987. "Algorithms for the Vehicle Routing and Scheduling Problems with Time Window Constraints," Operations Research, INFORMS, vol. 35(2), pages 254-265, April.
    17. Jan Fabian Ehmke, 2012. "Integration of Information and Optimization Models for Routing in City Logistics," International Series in Operations Research and Management Science, Springer, edition 127, number 978-1-4614-3628-7, December.
    18. Jan Fabian Ehmke, 2012. "Routing in City Logistics," International Series in Operations Research & Management Science, in: Integration of Information and Optimization Models for Routing in City Logistics, edition 127, chapter 0, pages 119-156, Springer.
    19. Koç, Çağrı & Bektaş, Tolga & Jabali, Ola & Laporte, Gilbert, 2016. "The impact of depot location, fleet composition and routing on emissions in city logistics," Transportation Research Part B: Methodological, Elsevier, vol. 84(C), pages 81-102.
    20. Demir, Emrah & Bektaş, Tolga & Laporte, Gilbert, 2014. "The bi-objective Pollution-Routing Problem," European Journal of Operational Research, Elsevier, vol. 232(3), pages 464-478.
    21. W Maden & R Eglese & D Black, 2010. "Vehicle routing and scheduling with time-varying data: A case study," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(3), pages 515-522, March.
    22. 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.
    23. Taesung Hwang & Yanfeng Ouyang, 2015. "Urban Freight Truck Routing under Stochastic Congestion and Emission Considerations," Sustainability, MDPI, vol. 7(6), pages 1-16, May.
    24. 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.
    25. Maria Battarra & Güneş Erdoğan & Daniele Vigo, 2014. "Exact Algorithms for the Clustered Vehicle Routing Problem," Operations Research, INFORMS, vol. 62(1), pages 58-71, February.
    26. Xiao, Yiyong & Konak, Abdullah, 2016. "The heterogeneous green vehicle routing and scheduling problem with time-varying traffic congestion," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 88(C), pages 146-166.
    27. 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.
    28. 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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    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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    7. Dongqing Zhang & Zhaoxia Guo, 2019. "On the Necessity and Effects of Considering Correlated Stochastic Speeds in Shortest Path Problems Under Sustainable Environments," Sustainability, MDPI, vol. 12(1), pages 1-14, December.
    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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