IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v197y2009i3p1185-1191.html
   My bibliography  Save this article

Ant colony optimization with a specialized pheromone trail for the car-sequencing problem

Author

Listed:
  • Morin, Sara
  • Gagné, Caroline
  • Gravel, Marc

Abstract

This paper studies the learning process in an ant colony optimization algorithm designed to solve the problem of ordering cars on an assembly line (car-sequencing problem). This problem has been shown to be NP-hard and evokes a great deal of interest among practitioners. Learning in an ant algorithm is achieved by using an artificial pheromone trail, which is a central element of this metaheuristic. Many versions of the algorithm are found in literature, the main distinction among them being the management of the pheromone trail. Nevertheless, few of them seek to perfect learning by modifying the internal structure of the trail. In this paper, a new pheromone trail structure is proposed that is specifically adapted to the type of constraints in the car-sequencing problem. The quality of the results obtained when solving three sets of benchmark problems is superior to that of the best solutions found in literature and shows the efficiency of the specialized trail.

Suggested Citation

  • Morin, Sara & Gagné, Caroline & Gravel, Marc, 2009. "Ant colony optimization with a specialized pheromone trail for the car-sequencing problem," European Journal of Operational Research, Elsevier, vol. 197(3), pages 1185-1191, September.
    • Handle: RePEc:eee:ejores:v:197:y:2009:i:3:p:1185-1191
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(08)00310-X
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Smith, Kate & Palaniswami, M. & Krishnamoorthy, M., 1996. "Traditional heuristic versus Hopfield neural network approaches to a car sequencing problem," European Journal of Operational Research, Elsevier, vol. 93(2), pages 300-316, September.
    2. M Gravel & C Gagné & W L Price, 2005. "Review and comparison of three methods for the solution of the car sequencing problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(11), pages 1287-1295, November.
    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. Zhang, Rui & Chang, Pei-Chann & Wu, Cheng, 2013. "A hybrid genetic algorithm for the job shop scheduling problem with practical considerations for manufacturing costs: Investigations motivated by vehicle production," International Journal of Production Economics, Elsevier, vol. 145(1), pages 38-52.
    2. Florian Jaehn & Sergey Kovalev & Mikhail Y. Kovalyov & Erwin Pesch, 2014. "Multiproduct batching and scheduling with buffered rework: The case of a car paint shop," Naval Research Logistics (NRL), John Wiley & Sons, vol. 61(6), pages 458-471, September.

    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. C Gagné & M Gravel & S Morin & W L Price, 2008. "Impact of the pheromone trail on the performance of ACO algorithms for solving the car-sequencing problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(8), pages 1077-1090, August.
    2. Boysen, Nils & Fliedner, Malte & Scholl, Armin, 2009. "Sequencing mixed-model assembly lines: Survey, classification and model critique," European Journal of Operational Research, Elsevier, vol. 192(2), pages 349-373, January.
    3. Cordeau, Jean-François & Laporte, Gilbert & Pasin, Federico, 2008. "Iterated tabu search for the car sequencing problem," European Journal of Operational Research, Elsevier, vol. 191(3), pages 945-956, December.
    4. Giard, Vincent & Jeunet, Jully, 2010. "Optimal sequencing of mixed models with sequence-dependent setups and utility workers on an assembly line," International Journal of Production Economics, Elsevier, vol. 123(2), pages 290-300, February.
    5. Boysen, Nils & Fliedner, Malte, 2007. "Comments on "Solving real car sequencing problems with ant colony optimization"," European Journal of Operational Research, Elsevier, vol. 182(1), pages 466-468, October.
    6. Elif Elcin Gunay & Ufuk Kula, 2017. "A stochastic programming model for resequencing buffer content optimisation in mixed-model assembly lines," International Journal of Production Research, Taylor & Francis Journals, vol. 55(10), pages 2897-2912, May.
    7. Joaquín Bautista & Jordi Pereira & Belarmino Adenso-Díaz, 2008. "A Beam Search approach for the optimization version of the Car Sequencing Problem," Annals of Operations Research, Springer, vol. 159(1), pages 233-244, March.
    8. Uli Golle & Franz Rothlauf & Nils Boysen, 2015. "Iterative beam search for car sequencing," Annals of Operations Research, Springer, vol. 226(1), pages 239-254, March.
    9. Solnon, Christine & Cung, Van Dat & Nguyen, Alain & Artigues, Christian, 2008. "The car sequencing problem: Overview of state-of-the-art methods and industrial case-study of the ROADEF'2005 challenge problem," European Journal of Operational Research, Elsevier, vol. 191(3), pages 912-927, December.
    10. Gagne, Caroline & Gravel, Marc & Price, Wilson L., 2006. "Solving real car sequencing problems with ant colony optimization," European Journal of Operational Research, Elsevier, vol. 174(3), pages 1427-1448, November.
    11. Parames Chutima & Sathaporn Olarnviwatchai, 2018. "A multi-objective car sequencing problem on two-sided assembly lines," Journal of Intelligent Manufacturing, Springer, vol. 29(7), pages 1617-1636, October.
    12. Prandtstetter, Matthias & Raidl, Günther R., 2008. "An integer linear programming approach and a hybrid variable neighborhood search for the car sequencing problem," European Journal of Operational Research, Elsevier, vol. 191(3), pages 1004-1022, December.
    13. Iwona Paprocka & Damian Krenczyk, 2023. "On Energy Consumption and Productivity in a Mixed-Model Assembly Line Sequencing Problem," Energies, MDPI, vol. 16(20), pages 1-19, October.
    14. El-Bouri, Ahmed & Balakrishnan, Subramaniam & Popplewell, Neil, 2000. "Sequencing jobs on a single machine: A neural network approach," European Journal of Operational Research, Elsevier, vol. 126(3), pages 474-490, November.
    15. Zhang, Rui & Chang, Pei-Chann & Wu, Cheng, 2013. "A hybrid genetic algorithm for the job shop scheduling problem with practical considerations for manufacturing costs: Investigations motivated by vehicle production," International Journal of Production Economics, Elsevier, vol. 145(1), pages 38-52.
    16. Fliedner, Malte & Boysen, Nils, 2008. "Solving the car sequencing problem via Branch & Bound," European Journal of Operational Research, Elsevier, vol. 191(3), pages 1023-1042, December.
    17. Benoist, Thierry, 2008. "Soft car sequencing with colors: Lower bounds and optimality proofs," European Journal of Operational Research, Elsevier, vol. 191(3), pages 957-971, December.
    18. Estellon, Bertrand & Gardi, Frédéric & Nouioua, Karim, 2008. "Two local search approaches for solving real-life car sequencing problems," European Journal of Operational Research, Elsevier, vol. 191(3), pages 928-944, December.
    19. Bautista, Joaquin & Cano, Jaime, 2008. "Minimizing work overload in mixed-model assembly lines," International Journal of Production Economics, Elsevier, vol. 112(1), pages 177-191, March.
    20. Bautista, Joaquín & Cano, Alberto, 2011. "Solving mixed model sequencing problem in assembly lines with serial workstations with work overload minimisation and interruption rules," European Journal of Operational Research, Elsevier, vol. 210(3), pages 495-513, May.

    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:eee:ejores:v:197:y:2009:i:3:p:1185-1191. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    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.