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A Multi-Objective Genetic Algorithm for the Vehicle Routing with Time Windows and Loading Problem

In: Intelligent Decision Support

Author

Listed:
  • Ana Moura

    (University of Aveiro
    Institute for Systems and Computers Engeneering)

Abstract

This work presents the Vehicle Routing with Time Windows and Loading Problem (VRTWLP) as a multi-objective optimization problem, implemented within a Genetic Algorithm. Specifically, the three dimensions of the problem to be optimized — the number of vehicles, the total travel distance and volume utilization — are considered to be separated dimensions of a multi-objective space. The quality of the solution obtained using this approach is evaluated and compared with results of other heuristic approaches previously developed by the author. The most significant contribution of this work is our interpretation of VRTWLP as a Multi-objective Optimization Problem.

Suggested Citation

  • Ana Moura, 2008. "A Multi-Objective Genetic Algorithm for the Vehicle Routing with Time Windows and Loading Problem," Springer Books, in: Andreas Bortfeldt & Jörg Homberger & Herbert Kopfer & Giselher Pankratz & Reinhard Strangmeier (ed.), Intelligent Decision Support, pages 187-201, Springer.
    • Handle: RePEc:spr:sprchp:978-3-8349-9777-7_11
    DOI: 10.1007/978-3-8349-9777-7_11
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    Citations

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    Cited by:

    1. Corinna Krebs & Jan Fabian Ehmke & Henriette Koch, 2021. "Advanced loading constraints for 3D vehicle routing problems," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(4), pages 835-875, December.
    2. Henriette Koch & Maximilian Schlögell & Andreas Bortfeldt, 2020. "A hybrid algorithm for the vehicle routing problem with three-dimensional loading constraints and mixed backhauls," Journal of Scheduling, Springer, vol. 23(1), pages 71-93, February.
    3. Corinna Krebs & Jan Fabian Ehmke, 2023. "Solution validator and visualizer for (combined) vehicle routing and container loading problems," Annals of Operations Research, Springer, vol. 326(1), pages 561-579, July.
    4. Rajaei, Maryam & Moslehi, Ghasem & Reisi-Nafchi, Mohammad, 2022. "The split heterogeneous vehicle routing problem with three-dimensional loading constraints on a large scale," European Journal of Operational Research, Elsevier, vol. 299(2), pages 706-721.
    5. Henriette Koch & Andreas Bortfeldt & Gerhard Wäscher, 2018. "A hybrid algorithm for the vehicle routing problem with backhauls, time windows and three-dimensional loading constraints," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(4), pages 1029-1075, October.
    6. Zongyi Chen & Mingkang Yang & Yijun Guo & Yu Liang & Yifan Ding & Li Wang, 2020. "The Split Delivery Vehicle Routing Problem with Three-Dimensional Loading and Time Windows Constraints," Sustainability, MDPI, vol. 12(17), pages 1-21, August.
    7. Henriette Koch & Andreas Bortfeldt & Gerhard Wäscher, 2017. "A hybrid solution approach for the 3L-VRP with simultaneous delivery and pickups," FEMM Working Papers 170005, Otto-von-Guericke University Magdeburg, Faculty of Economics and Management.
    8. Selma Khebbache-Hadji & Christian Prins & Alice Yalaoui & Mohamed Reghioui, 2013. "Heuristics and memetic algorithm for the two-dimensional loading capacitated vehicle routing problem with time windows," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 21(2), pages 307-336, March.

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