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Individually Optimized Commercial Road Transport: A Decision Support System for Customizable Routing Problems

Author

Listed:
  • Max Leyerer

    (School of Economics and Management, Leibniz University Hannover, 30167 Hannover, Germany)

  • Marc-Oliver Sonneberg

    (School of Economics and Management, Leibniz University Hannover, 30167 Hannover, Germany)

  • Maximilian Heumann

    (School of Economics and Management, Leibniz University Hannover, 30167 Hannover, Germany)

  • Tim Kammann

    (School of Economics and Management, Leibniz University Hannover, 30167 Hannover, Germany)

  • Michael H. Breitner

    (School of Economics and Management, Leibniz University Hannover, 30167 Hannover, Germany)

Abstract

The Vehicle Routing Problem (VRP) in its manifold variants is widely discussed in scientific literature. We investigate related optimization models and solution methods to determine the state of research for vehicle routing attributes and their combinations. Most of these approaches are idealized and focus on single problem-tailored routing applications. Addressing this research gap, we present a customizable VRP for optimized road transportation embedded into a Decision Support System (DSS). It integrates various model attributes and handles a multitude of real-world routing problems. In the context of urban logistics, practitioners of different industries and researchers are assisted in efficient route planning that allows for minimizing driving distances and reducing vehicle emissions. Based on the design science research methodology, we evaluate the DSS with computational benchmarks and real-world simulations. Results indicate that our developed DSS can compete with problem-tailored algorithms. With our solution-oriented DSS as final artifact, we contribute to an enhanced economic and environmental sustainability in urban logistic applications.

Suggested Citation

  • Max Leyerer & Marc-Oliver Sonneberg & Maximilian Heumann & Tim Kammann & Michael H. Breitner, 2019. "Individually Optimized Commercial Road Transport: A Decision Support System for Customizable Routing Problems," Sustainability, MDPI, vol. 11(20), pages 1-21, October.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:20:p:5544-:d:274362
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    References listed on IDEAS

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    1. Thibaut Vidal & Teodor Gabriel Crainic & Michel Gendreau & Nadia Lahrichi & Walter Rei, 2012. "A Hybrid Genetic Algorithm for Multidepot and Periodic Vehicle Routing Problems," Operations Research, INFORMS, vol. 60(3), pages 611-624, June.
    2. Lahyani, Rahma & Khemakhem, Mahdi & Semet, Frédéric, 2015. "Rich vehicle routing problems: From a taxonomy to a definition," European Journal of Operational Research, Elsevier, vol. 241(1), pages 1-14.
    3. Diego Cattaruzza & Nabil Absi & Dominique Feillet, 2016. "The Multi-Trip Vehicle Routing Problem with Time Windows and Release Dates," Transportation Science, INFORMS, vol. 50(2), pages 676-693, May.
    4. Coelho, V.N. & Grasas, A. & Ramalhinho, H. & Coelho, I.M. & Souza, M.J.F. & Cruz, R.C., 2016. "An ILS-based algorithm to solve a large-scale real heterogeneous fleet VRP with multi-trips and docking constraints," European Journal of Operational Research, Elsevier, vol. 250(2), pages 367-376.
    5. Rasmussen, Matias Sevel & Justesen, Tor & Dohn, Anders & Larsen, Jesper, 2012. "The Home Care Crew Scheduling Problem: Preference-based visit clustering and temporal dependencies," European Journal of Operational Research, Elsevier, vol. 219(3), pages 598-610.
    6. Olli Bräysy & Michel Gendreau, 2005. "Vehicle Routing Problem with Time Windows, Part I: Route Construction and Local Search Algorithms," Transportation Science, INFORMS, vol. 39(1), pages 104-118, February.
    7. Julia Rieck & Jürgen Zimmermann, 2010. "A new mixed integer linear model for a rich vehicle routing problem with docking constraints," Annals of Operations Research, Springer, vol. 181(1), pages 337-358, December.
    8. Schmid, Verena & Doerner, Karl F. & Laporte, Gilbert, 2013. "Rich routing problems arising in supply chain management," European Journal of Operational Research, Elsevier, vol. 224(3), pages 435-448.
    9. Chuck Holland & Jack Levis & Ranganath Nuggehalli & Bob Santilli & Jeff Winters, 2017. "UPS Optimizes Delivery Routes," Interfaces, INFORMS, vol. 47(1), pages 8-23, February.
    10. Attila A. Kovacs & Bruce L. Golden & Richard F. Hartl & Sophie N. Parragh, 2015. "The Generalized Consistent Vehicle Routing Problem," Transportation Science, INFORMS, vol. 49(4), pages 796-816, November.
    11. Christian Prins & Caroline Prodhon & Angel Ruiz & Patrick Soriano & Roberto Wolfler Calvo, 2007. "Solving the Capacitated Location-Routing Problem by a Cooperative Lagrangean Relaxation-Granular Tabu Search Heuristic," Transportation Science, INFORMS, vol. 41(4), pages 470-483, November.
    12. Gilbert Laporte, 2009. "Fifty Years of Vehicle Routing," Transportation Science, INFORMS, vol. 43(4), pages 408-416, November.
    13. Richard Hartl & Geir Hasle & Gerrit Janssens, 2006. "Special issue on Rich Vehicle Routing Problems," 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. 14(2), pages 103-104, June.
    14. J-F Cordeau & M Gendreau & G Laporte & J-Y Potvin & F Semet, 2002. "A guide to vehicle routing heuristics," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(5), pages 512-522, May.
    15. Diego Cattaruzza & Nabil Absi & Dominique Feillet & Jesús González-Feliu, 2017. "Vehicle routing problems for city logistics," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 6(1), pages 51-79, March.
    16. Soysal, Mehmet & Bloemhof-Ruwaard, Jacqueline M. & Bektaş, Tolga, 2015. "The time-dependent two-echelon capacitated vehicle routing problem with environmental considerations," International Journal of Production Economics, Elsevier, vol. 164(C), pages 366-378.
    17. Laporte, Gilbert, 1992. "The vehicle routing problem: An overview of exact and approximate algorithms," European Journal of Operational Research, Elsevier, vol. 59(3), pages 345-358, June.
    18. Rais, A. & Alvelos, F. & Carvalho, M.S., 2014. "New mixed integer-programming model for the pickup-and-delivery problem with transshipment," European Journal of Operational Research, Elsevier, vol. 235(3), pages 530-539.
    19. Rafael E. Aleman & Xinhui Zhang & Raymond R. Hill, 2009. "A ring-based diversification scheme for routing problems," International Journal of Mathematics in Operational Research, Inderscience Enterprises Ltd, vol. 1(1/2), pages 163-190.
    20. J. M. Belenguer & M. C. Martinez & E. Mota, 2000. "A Lower Bound for the Split Delivery Vehicle Routing Problem," Operations Research, INFORMS, vol. 48(5), pages 801-810, October.
    21. Alberto Ceselli & Giovanni Righini & Matteo Salani, 2009. "A Column Generation Algorithm for a Rich Vehicle-Routing Problem," Transportation Science, INFORMS, vol. 43(1), pages 56-69, February.
    22. Pedro Amorim & Sophie Parragh & Fabrício Sperandio & Bernardo Almada-Lobo, 2014. "A rich vehicle routing problem dealing with perishable food: a case study," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(2), pages 489-508, July.
    23. Angel Ibeas & Jose L. Moura & Luigi dell'Olio, 2009. "Planning school transport: design of routes with flexible school opening times," Transportation Planning and Technology, Taylor & Francis Journals, vol. 32(6), pages 527-544, September.
    24. Stenger, A. & Schneider, M. & Goeke, D., 2013. "The Prize-Collecting Vehicle Routing Problem with Single and Multiple Depots and Non-Linear Cost," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 62372, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
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