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Vehicle routing with transportable resources: Using carpooling and walking for on-site services

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  • Coindreau, Marc-Antoine
  • Gallay, Olivier
  • Zufferey, Nicolas

Abstract

In the classical Vehicle Routing Problem (VRP), it is assumed that each worker moves using an individually assigned vehicle. Removing this core hypothesis opens the door for a brand new set of solutions, where workers are seen as transportable resources that can also move without the help of a vehicle. In this context, motivated by a major European energy provider, we consider a situation where workers can either walk or drive to reach a job and where carpooling is enabled. In order to quantify the potential benefits offered by this new framework, a dedicated Variable Neighborhood Search is proposed to efficiently tackle the underlying synchronization and precedence constraints that arise in this extension of the VRP. Considering a set of instances in an urban context, extensive computational experiments show that, despite conservative scenarios favoring car mobility, significant savings are achieved when compared to the solutions currently obtained by the involved company. This innovative formulation allows managers to reduce the size of the vehicle fleet while keeping the number of workers stable and, surprisingly, decreasing the overall driving distance simultaneously.

Suggested Citation

  • Coindreau, Marc-Antoine & Gallay, Olivier & Zufferey, Nicolas, 2019. "Vehicle routing with transportable resources: Using carpooling and walking for on-site services," European Journal of Operational Research, Elsevier, vol. 279(3), pages 996-1010.
  • Handle: RePEc:eee:ejores:v:279:y:2019:i:3:p:996-1010
    DOI: 10.1016/j.ejor.2019.06.039
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    References listed on IDEAS

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    1. Grangier, Philippe & Gendreau, Michel & Lehuédé, Fabien & Rousseau, Louis-Martin, 2016. "An adaptive large neighborhood search for the two-echelon multiple-trip vehicle routing problem with satellite synchronization," European Journal of Operational Research, Elsevier, vol. 254(1), pages 80-91.
    2. Guy Desaulniers & François Lessard & Ahmed Hadjar, 2008. "Tabu Search, Partial Elementarity, and Generalized k -Path Inequalities for the Vehicle Routing Problem with Time Windows," Transportation Science, INFORMS, vol. 42(3), pages 387-404, August.
    3. Boysen, Nils & Schwerdfeger, Stefan & Weidinger, Felix, 2018. "Scheduling last-mile deliveries with truck-based autonomous robots," European Journal of Operational Research, Elsevier, vol. 271(3), pages 1085-1099.
    4. 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.
    5. Pillac, Victor & Gendreau, Michel & Guéret, Christelle & Medaglia, Andrés L., 2013. "A review of dynamic vehicle routing problems," European Journal of Operational Research, Elsevier, vol. 225(1), pages 1-11.
    6. Stefan Ropke & David Pisinger, 2006. "An Adaptive Large Neighborhood Search Heuristic for the Pickup and Delivery Problem with Time Windows," Transportation Science, INFORMS, vol. 40(4), pages 455-472, November.
    7. Boysen, Nils & Schwerdfeger, Stefan & Weidinger, Felix, 2018. "Scheduling last-mile deliveries with truck-based autonomous robots," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 126189, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    8. Niels Agatz & Paul Bouman & Marie Schmidt, 2018. "Optimization Approaches for the Traveling Salesman Problem with Drone," Transportation Science, INFORMS, vol. 52(4), pages 965-981, August.
    9. Lu, Da & Gzara, Fatma, 2019. "The robust vehicle routing problem with time windows: Solution by branch and price and cut," European Journal of Operational Research, Elsevier, vol. 275(3), pages 925-938.
    10. Michael Drexl, 2012. "Synchronization in Vehicle Routing---A Survey of VRPs with Multiple Synchronization Constraints," Transportation Science, INFORMS, vol. 46(3), pages 297-316, August.
    11. Baldacci, Roberto & Mingozzi, Aristide & Roberti, Roberto, 2012. "Recent exact algorithms for solving the vehicle routing problem under capacity and time window constraints," European Journal of Operational Research, Elsevier, vol. 218(1), pages 1-6.
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    5. Themistoklis Stamadianos & Nikolaos A. Kyriakakis & Magdalene Marinaki & Yannis Marinakis, 2023. "Routing Problems with Electric and Autonomous Vehicles: Review and Potential for Future Research," SN Operations Research Forum, Springer, vol. 4(2), pages 1-34, June.
    6. Antonio Martinez-Sykora & Fraser McLeod & Carlos Lamas-Fernandez & Tolga Bektaş & Tom Cherrett & Julian Allen, 2020. "Optimised solutions to the last-mile delivery problem in London using a combination of walking and driving," Annals of Operations Research, Springer, vol. 295(2), pages 645-693, December.
    7. Jin Li & Hongping Zhang & Huasheng Liu & Shiyan Wang, 2024. "Multi-Objective Planning of Commuter Carpooling under Time-Varying Road Network," Sustainability, MDPI, vol. 16(2), pages 1-16, January.

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