IDEAS home Printed from https://ideas.repec.org/a/spr/jcomop/v24y2012i4d10.1007_s10878-011-9400-8.html
   My bibliography  Save this article

Self-organizing maps in population based metaheuristic to the dynamic vehicle routing problem

Author

Listed:
  • Jean-Charles Créput

    (U.T.B.M.)

  • Amir Hajjam

    (U.T.B.M.)

  • Abderrafiaa Koukam

    (U.T.B.M.)

  • Olivier Kuhn

    (Bât. Nautibus)

Abstract

We consider the dynamic vehicle routing problem (dynamic VRP). In this problem, new customer demands are received along the day. Hence, they must be serviced at their locations by a set of vehicles in real time. The approach to address the problem is a hybrid method which manipulates the self-organizing map (SOM) neural network into a population based evolutionary algorithm. The method, called memetic SOM, illustrates how the concept of intermediate structure, also called elastic net or adaptive mesh concept, provided by the original SOM can naturally be applied into a dynamic setting. The experiments show that the heuristic outperforms the approaches that were applied to the Kilby et al. 22 problems with up to 385 customers. It performs better with respect to solution quality than the ant colony algorithm MACS-VRPTW, a genetic algorithm, and a multi-agent oriented approach, with a computation time used roughly 100 times lesser.

Suggested Citation

  • Jean-Charles Créput & Amir Hajjam & Abderrafiaa Koukam & Olivier Kuhn, 2012. "Self-organizing maps in population based metaheuristic to the dynamic vehicle routing problem," Journal of Combinatorial Optimization, Springer, vol. 24(4), pages 437-458, November.
    • Handle: RePEc:spr:jcomop:v:24:y:2012:i:4:d:10.1007_s10878-011-9400-8
    DOI: 10.1007/s10878-011-9400-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10878-011-9400-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10878-011-9400-8?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 & François Guertin & Jean-Yves Potvin & Éric Taillard, 1999. "Parallel Tabu Search for Real-Time Vehicle Routing and Dispatching," Transportation Science, INFORMS, vol. 33(4), pages 381-390, November.
    2. Gerhard Reinelt, 1991. "TSPLIB—A Traveling Salesman Problem Library," INFORMS Journal on Computing, INFORMS, vol. 3(4), pages 376-384, November.
    3. Dimitris J. Bertsimas & David Simchi-Levi, 1996. "A New Generation of Vehicle Routing Research: Robust Algorithms, Addressing Uncertainty," Operations Research, INFORMS, vol. 44(2), pages 286-304, April.
    4. Helsgaun, Keld, 2000. "An effective implementation of the Lin-Kernighan traveling salesman heuristic," European Journal of Operational Research, Elsevier, vol. 126(1), pages 106-130, October.
    5. Jean-François Cordeau & Michel Gendreau & Alain Hertz & Gilbert Laporte & Jean-Sylvain Sormany, 2005. "New Heuristics for the Vehicle Routing Problem," Springer Books, in: André Langevin & Diane Riopel (ed.), Logistics Systems: Design and Optimization, chapter 0, pages 279-297, Springer.
    6. Ghiani, Gianpaolo & Guerriero, Francesca & Laporte, Gilbert & Musmanno, Roberto, 2003. "Real-time vehicle routing: Solution concepts, algorithms and parallel computing strategies," European Journal of Operational Research, Elsevier, vol. 151(1), pages 1-11, November.
    7. R. Montemanni & L. M. Gambardella & A. E. Rizzoli & A. V. Donati, 2005. "Ant Colony System for a Dynamic Vehicle Routing Problem," Journal of Combinatorial Optimization, Springer, vol. 10(4), pages 327-343, December.
    8. Russell W. Bent & Pascal Van Hentenryck, 2004. "Scenario-Based Planning for Partially Dynamic Vehicle Routing with Stochastic Customers," Operations Research, INFORMS, vol. 52(6), pages 977-987, December.
    9. 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.
    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. Guiwu Xiong & Yong Wang, 2014. "Best routes selection in multimodal networks using multi-objective genetic algorithm," Journal of Combinatorial Optimization, Springer, vol. 28(3), pages 655-673, October.
    2. He Huang & Po-Chou Shih & Yuelan Zhu & Wei Gao, 2022. "An integrated model for medical expense system optimization during diagnosis process based on artificial intelligence algorithm," Journal of Combinatorial Optimization, Springer, vol. 44(4), pages 2515-2532, November.

    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. 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.
    2. Roberto Tadei & Guido Perboli & Francesca Perfetti, 2017. "The multi-path Traveling Salesman Problem with stochastic travel costs," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 6(1), pages 3-23, March.
    3. Zhang, Jian & Woensel, Tom Van, 2023. "Dynamic vehicle routing with random requests: A literature review," International Journal of Production Economics, Elsevier, vol. 256(C).
    4. Marcel Turkensteen & Dmitry Malyshev & Boris Goldengorin & Panos M. Pardalos, 2017. "The reduction of computation times of upper and lower tolerances for selected combinatorial optimization problems," Journal of Global Optimization, Springer, vol. 68(3), pages 601-622, July.
    5. Baris Yildiz & Martin Savelsbergh, 2019. "Provably High-Quality Solutions for the Meal Delivery Routing Problem," Transportation Science, INFORMS, vol. 53(5), pages 1372-1388, September.
    6. Gary R. Waissi & Pragya Kaushal, 2020. "A polynomial matrix processing heuristic algorithm for finding high quality feasible solutions for the TSP," OPSEARCH, Springer;Operational Research Society of India, vol. 57(1), pages 73-87, March.
    7. Cheung, Bernard K.-S. & Choy, K.L. & Li, Chung-Lun & Shi, Wenzhong & Tang, Jian, 2008. "Dynamic routing model and solution methods for fleet management with mobile technologies," International Journal of Production Economics, Elsevier, vol. 113(2), pages 694-705, June.
    8. Briseida Sarasola & Karl Doerner & Verena Schmid & Enrique Alba, 2016. "Variable neighborhood search for the stochastic and dynamic vehicle routing problem," Annals of Operations Research, Springer, vol. 236(2), pages 425-461, January.
    9. Chen, Lichun & Miller-Hooks, Elise, 2012. "Optimal team deployment in urban search and rescue," Transportation Research Part B: Methodological, Elsevier, vol. 46(8), pages 984-999.
    10. Ferrucci, Francesco & Bock, Stefan & Gendreau, Michel, 2013. "A pro-active real-time control approach for dynamic vehicle routing problems dealing with the delivery of urgent goods," European Journal of Operational Research, Elsevier, vol. 225(1), pages 130-141.
    11. William Cook & Daniel G. Espinoza & Marcos Goycoolea, 2007. "Computing with Domino-Parity Inequalities for the Traveling Salesman Problem (TSP)," INFORMS Journal on Computing, INFORMS, vol. 19(3), pages 356-365, August.
    12. E. Angelelli & R. Mansini & M. Vindigni, 2016. "The Stochastic and Dynamic Traveling Purchaser Problem," Transportation Science, INFORMS, vol. 50(2), pages 642-658, May.
    13. Briseida Sarasola & Karl F. Doerner & Verena Schmid & Enrique Alba, 2016. "Variable neighborhood search for the stochastic and dynamic vehicle routing problem," Annals of Operations Research, Springer, vol. 236(2), pages 425-461, January.
    14. K Sang-Ho & G Young-Gun & K Maing-Kyu, 2003. "Application of the out-of-kilter algorithm to the asymmetric traveling salesman problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(10), pages 1085-1092, October.
    15. Barrett W. Thomas, 2007. "Waiting Strategies for Anticipating Service Requests from Known Customer Locations," Transportation Science, INFORMS, vol. 41(3), pages 319-331, August.
    16. William Cook & Paul Seymour, 2003. "Tour Merging via Branch-Decomposition," INFORMS Journal on Computing, INFORMS, vol. 15(3), pages 233-248, August.
    17. L Vogt & C A Poojari & J E Beasley, 2007. "A tabu search algorithm for the single vehicle routing allocation problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(4), pages 467-480, April.
    18. Burger, M. & Su, Z. & De Schutter, B., 2018. "A node current-based 2-index formulation for the fixed-destination multi-depot travelling salesman problem," European Journal of Operational Research, Elsevier, vol. 265(2), pages 463-477.
    19. Schyns, M., 2015. "An ant colony system for responsive dynamic vehicle routing," European Journal of Operational Research, Elsevier, vol. 245(3), pages 704-718.
    20. S. F. Ghannadpour & S. Noori & R. Tavakkoli-Moghaddam, 2014. "A multi-objective vehicle routing and scheduling problem with uncertainty in customers’ request and priority," Journal of Combinatorial Optimization, Springer, vol. 28(2), pages 414-446, August.

    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:spr:jcomop:v:24:y:2012:i:4:d:10.1007_s10878-011-9400-8. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.