IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v55y2017i4p1100-1116.html
   My bibliography  Save this article

Modelling and solution of a large-scale vehicle routing problem at GE appliances & lighting

Author

Listed:
  • Ehsan Khodabandeh
  • Lihui Bai
  • Sunderesh S. Heragu
  • Gerald W. Evans
  • Thomas Elrod
  • Mark Shirkness

Abstract

We consider a special case of the vehicle routing problem where not only each customer has specified delivery time window, but each route has limited time duration. We propose a solution algorithm using network reduction techniques and simulated annealing meta-heuristic. The objective is twofold: minimising the travel time and minimising the total number of vehicles required. The time-window constraint ensures delivery without delay, thus, a potentially higher level of customer satisfaction. The algorithm has helped the transportation planning team at General Electric Appliances & Lighting to significantly reduce the number of required trucks in two real cases, while its performance on randomly generated cases is also efficient when compared to properly selected benchmarking algorithms.

Suggested Citation

  • Ehsan Khodabandeh & Lihui Bai & Sunderesh S. Heragu & Gerald W. Evans & Thomas Elrod & Mark Shirkness, 2017. "Modelling and solution of a large-scale vehicle routing problem at GE appliances & lighting," International Journal of Production Research, Taylor & Francis Journals, vol. 55(4), pages 1100-1116, February.
    • Handle: RePEc:taf:tprsxx:v:55:y:2017:i:4:p:1100-1116
    DOI: 10.1080/00207543.2016.1220685
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2016.1220685
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00207543.2016.1220685?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Michel Gendreau & Alain Hertz & Gilbert Laporte & Mihnea Stan, 1998. "A Generalized Insertion Heuristic for the Traveling Salesman Problem with Time Windows," Operations Research, INFORMS, vol. 46(3), pages 330-335, June.
    2. 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.
    3. Olli Bräysy & Michel Gendreau, 2005. "Vehicle Routing Problem with Time Windows, Part II: Metaheuristics," Transportation Science, INFORMS, vol. 39(1), pages 119-139, February.
    4. A Ostertag & K F Doerner & R F Hartl & E D Taillard & P Waelti, 2009. "POPMUSIC for a real-world large-scale vehicle routing problem with time windows," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(7), pages 934-943, July.
    5. Özdamar, Linet & Demir, Onur, 2012. "A hierarchical clustering and routing procedure for large scale disaster relief logistics planning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(3), pages 591-602.
    6. J-F Cordeau & G Laporte & A Mercier, 2004. "Improved tabu search algorithm for the handling of route duration constraints in vehicle routing problems with time windows," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(5), pages 542-546, May.
    7. Qi, Mingyao & Lin, Wei-Hua & Li, Nan & Miao, Lixin, 2012. "A spatiotemporal partitioning approach for large-scale vehicle routing problems with time windows," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(1), pages 248-257.
    8. Russell Bent & Pascal Van Hentenryck, 2004. "A Two-Stage Hybrid Local Search for the Vehicle Routing Problem with Time Windows," Transportation Science, INFORMS, vol. 38(4), pages 515-530, November.
    9. Dondo, Rodolfo & Cerda, Jaime, 2007. "A cluster-based optimization approach for the multi-depot heterogeneous fleet vehicle routing problem with time windows," European Journal of Operational Research, Elsevier, vol. 176(3), pages 1478-1507, February.
    10. J-F Cordeau & G Laporte & A Mercier, 2001. "A unified tabu search heuristic for vehicle routing problems with time windows," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 52(8), pages 928-936, August.
    11. Martin W. P. Savelsbergh, 1992. "The Vehicle Routing Problem with Time Windows: Minimizing Route Duration," INFORMS Journal on Computing, INFORMS, vol. 4(2), pages 146-154, May.
    12. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xiaxia Ma & Wenliang Bian & Wenchao Wei & Fei Wei, 2022. "Customer-Centric, Two-Product Split Delivery Vehicle Routing Problem under Consideration of Weighted Customer Waiting Time in Power Industry," Energies, MDPI, vol. 15(10), pages 1-23, May.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Schneider, Michael, 2016. "The vehicle-routing problem with time windows and driver-specific times," European Journal of Operational Research, Elsevier, vol. 250(1), pages 101-119.
    2. Schneider, Michael & Schwahn, Fabian & Vigo, Daniele, 2017. "Designing granular solution methods for routing problems with time windows," European Journal of Operational Research, Elsevier, vol. 263(2), pages 493-509.
    3. Schneider, M., 2016. "The vehicle-routing problem with time windows and driver-specific times," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 65941, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    4. Michael Schneider & Andreas Stenger & Dominik Goeke, 2014. "The Electric Vehicle-Routing Problem with Time Windows and Recharging Stations," Transportation Science, INFORMS, vol. 48(4), pages 500-520, November.
    5. 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.
    6. Olli Bräysy & Michel Gendreau, 2005. "Vehicle Routing Problem with Time Windows, Part II: Metaheuristics," Transportation Science, INFORMS, vol. 39(1), pages 119-139, February.
    7. Drexl, Michael & Schneider, Michael, 2015. "A survey of variants and extensions of the location-routing problem," European Journal of Operational Research, Elsevier, vol. 241(2), pages 283-308.
    8. Mohamed Cissé & Semih Yalçindag & Yannick Kergosien & Evren Sahin & Christophe Lenté & Andrea Matta, 2017. "OR problems related to Home Health Care: A review of relevant routing and scheduling problems," Post-Print hal-01736714, HAL.
    9. Vidal, Thibaut & Crainic, Teodor Gabriel & Gendreau, Michel & Prins, Christian, 2013. "Heuristics for multi-attribute vehicle routing problems: A survey and synthesis," European Journal of Operational Research, Elsevier, vol. 231(1), pages 1-21.
    10. Shijin Wang & Xiaodong Wang & Xin Liu & Jianbo Yu, 2018. "A Bi-Objective Vehicle-Routing Problem with Soft Time Windows and Multiple Depots to Minimize the Total Energy Consumption and Customer Dissatisfaction," Sustainability, MDPI, vol. 10(11), pages 1-21, November.
    11. Liu, Ran & Xie, Xiaolan & Garaix, Thierry, 2014. "Hybridization of tabu search with feasible and infeasible local searches for periodic home health care logistics," Omega, Elsevier, vol. 47(C), pages 17-32.
    12. Alcaraz, Juan J. & Caballero-Arnaldos, Luis & Vales-Alonso, Javier, 2019. "Rich vehicle routing problem with last-mile outsourcing decisions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 129(C), pages 263-286.
    13. Nicolas Rincon-Garcia & Ben J. Waterson & Tom J. Cherrett, 2018. "Requirements from vehicle routing software: perspectives from literature, developers and the freight industry," Transport Reviews, Taylor & Francis Journals, vol. 38(1), pages 117-138, January.
    14. Qi, Mingyao & Lin, Wei-Hua & Li, Nan & Miao, Lixin, 2012. "A spatiotemporal partitioning approach for large-scale vehicle routing problems with time windows," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(1), pages 248-257.
    15. Jeffrey W. Ohlmann & Michael J. Fry & Barrett W. Thomas, 2008. "Route Design for Lean Production Systems," Transportation Science, INFORMS, vol. 42(3), pages 352-370, August.
    16. Dumez, Dorian & Lehuédé, Fabien & Péton, Olivier, 2021. "A large neighborhood search approach to the vehicle routing problem with delivery options," Transportation Research Part B: Methodological, Elsevier, vol. 144(C), pages 103-132.
    17. Dimitris Bertsimas & Patrick Jaillet, & Sébastien Martin, 2019. "Online Vehicle Routing: The Edge of Optimization in Large-Scale Applications," Operations Research, INFORMS, vol. 67(1), pages 143-162, January.
    18. Ehmke, Jan Fabian & Campbell, Ann Melissa, 2014. "Customer acceptance mechanisms for home deliveries in metropolitan areas," European Journal of Operational Research, Elsevier, vol. 233(1), pages 193-207.
    19. Pages, Laia & Jayakrishnan, R. & Cortes, Cristian E., 2005. "Real-Time Mass Passenger Transport Network Optimization Problems," University of California Transportation Center, Working Papers qt7w88d089, University of California Transportation Center.
    20. Bergmann, Felix M. & Wagner, Stephan M. & Winkenbach, Matthias, 2020. "Integrating first-mile pickup and last-mile delivery on shared vehicle routes for efficient urban e-commerce distribution," Transportation Research Part B: Methodological, Elsevier, vol. 131(C), pages 26-62.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:tprsxx:v:55:y:2017:i:4:p:1100-1116. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TPRS20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.