IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v183y2011i1p143-16110.1007-s10479-009-0545-0.html
   My bibliography  Save this article

A GRASP-based approach for technicians and interventions scheduling for telecommunications

Author

Listed:
  • Hideki Hashimoto
  • Sylvain Boussier
  • Michel Vasquez
  • Christophe Wilbaut

Abstract

The Technicians and Interventions Scheduling Problem for Telecommunications embeds the scheduling of interventions, the assignment of teams to interventions and the assignment of technicians to teams. Every intervention is characterized, among other attributes, by a priority. The objective of this problem is to schedule interventions such that the interventions with the highest priority are scheduled at the earliest time possible while satisfying a set of constraints like the precedence between some interventions and the minimum number of technicians needed with the required skill levels for the intervention. We present a Greedy Randomized Adaptive Search Procedure (GRASP) for solving this problem. In the proposed implementation, we integrate learning to the GRASP framework in order to generate good-quality solutions using information brought by previous ones. We also compute lower bounds and present experimental results that validate the effectiveness of this approach. Copyright Springer Science+Business Media, LLC 2011

Suggested Citation

  • Hideki Hashimoto & Sylvain Boussier & Michel Vasquez & Christophe Wilbaut, 2011. "A GRASP-based approach for technicians and interventions scheduling for telecommunications," Annals of Operations Research, Springer, vol. 183(1), pages 143-161, March.
    • Handle: RePEc:spr:annopr:v:183:y:2011:i:1:p:143-161:10.1007/s10479-009-0545-0
    DOI: 10.1007/s10479-009-0545-0
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10479-009-0545-0
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10479-009-0545-0?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. Taillard, Eric D. & Gambardella, Luca M. & Gendreau, Michel & Potvin, Jean-Yves, 2001. "Adaptive memory programming: A unified view of metaheuristics," European Journal of Operational Research, Elsevier, vol. 135(1), pages 1-16, November.
    2. Charles Fleurent & Fred Glover, 1999. "Improved Constructive Multistart Strategies for the Quadratic Assignment Problem Using Adaptive Memory," INFORMS Journal on Computing, INFORMS, vol. 11(2), pages 198-204, May.
    3. Andrea Lodi & Silvano Martello & Daniele Vigo, 2004. "Models and Bounds for Two-Dimensional Level Packing Problems," Journal of Combinatorial Optimization, Springer, vol. 8(3), pages 363-379, September.
    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. Ines Mathlouthi & Michel Gendreau & Jean-Yves Potvin, 2021. "Branch-and-Price for a Multi-attribute Technician Routing and Scheduling Problem," SN Operations Research Forum, Springer, vol. 2(1), pages 1-35, March.
    2. Nowak, Maciek & Szufel, Przemysław, 2024. "Technician routing and scheduling for the sharing economy," European Journal of Operational Research, Elsevier, vol. 314(1), pages 15-31.
    3. Chen, Xi & Thomas, Barrett W. & Hewitt, Mike, 2016. "The technician routing problem with experience-based service times," Omega, Elsevier, vol. 61(C), pages 49-61.
    4. Fangzhou Yan & Huaxin Qiu & Dongya Han, 2023. "Lagrangian Heuristic for Multi-Depot Technician Planning of Product Distribution and Installation with a Lunch Break," Mathematics, MDPI, vol. 11(3), pages 1-22, January.
    5. Michel Vasquez & Mirsad Buljubasic & Saïd Hanafi, 2023. "An efficient scenario penalization matheuristic for a stochastic scheduling problem," Journal of Heuristics, Springer, vol. 29(2), pages 383-408, June.
    6. Ehsan Pourjavad & Eman Almehdawe, 2022. "Optimization of the technician routing and scheduling problem for a telecommunication industry," Annals of Operations Research, Springer, vol. 315(1), pages 371-395, August.
    7. Paraskevopoulos, Dimitris C. & Laporte, Gilbert & Repoussis, Panagiotis P. & Tarantilis, Christos D., 2017. "Resource constrained routing and scheduling: Review and research prospects," European Journal of Operational Research, Elsevier, vol. 263(3), pages 737-754.

    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. E A Silver, 2004. "An overview of heuristic solution methods," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(9), pages 936-956, September.
    2. Michel Gendreau & Jean-Yves Potvin, 2005. "Metaheuristics in Combinatorial Optimization," Annals of Operations Research, Springer, vol. 140(1), pages 189-213, November.
    3. Loiola, Eliane Maria & de Abreu, Nair Maria Maia & Boaventura-Netto, Paulo Oswaldo & Hahn, Peter & Querido, Tania, 2007. "A survey for the quadratic assignment problem," European Journal of Operational Research, Elsevier, vol. 176(2), pages 657-690, January.
    4. Martí, Rafael & Resende, Mauricio G.C. & Ribeiro, Celso C., 2013. "Multi-start methods for combinatorial optimization," European Journal of Operational Research, Elsevier, vol. 226(1), pages 1-8.
    5. Jean-François Côté & Manuel Iori, 2018. "The Meet-in-the-Middle Principle for Cutting and Packing Problems," INFORMS Journal on Computing, INFORMS, vol. 30(4), pages 646-661, November.
    6. Angel Juan & Javier Faulin & Albert Ferrer & Helena Lourenço & Barry Barrios, 2013. "MIRHA: multi-start biased randomization of heuristics with adaptive local search for solving non-smooth routing problems," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(1), pages 109-132, April.
    7. Amalia I. Nikolopoulou & Panagiotis P. Repoussis & Christos D. Tarantilis & Emmanouil E. Zachariadis, 2019. "Adaptive memory programming for the many-to-many vehicle routing problem with cross-docking," Operational Research, Springer, vol. 19(1), pages 1-38, March.
    8. Dontas, Michael & Sideris, Georgios & Manousakis, Eleftherios G. & Zachariadis, Emmanouil E., 2023. "An adaptive memory matheuristic for the set orienteering problem," European Journal of Operational Research, Elsevier, vol. 309(3), pages 1010-1023.
    9. Celso C. Ribeiro & Eduardo Uchoa & Renato F. Werneck, 2002. "A Hybrid GRASP with Perturbations for the Steiner Problem in Graphs," INFORMS Journal on Computing, INFORMS, vol. 14(3), pages 228-246, August.
    10. Yi-Ping Cui & Yongwu Zhou & Yaodong Cui, 2017. "Triple-solution approach for the strip packing problem with two-staged patterns," Journal of Combinatorial Optimization, Springer, vol. 34(2), pages 588-604, August.
    11. El-Bouri, A. & Azizi, N. & Zolfaghari, S., 2007. "A comparative study of a new heuristic based on adaptive memory programming and simulated annealing: The case of job shop scheduling," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1894-1910, March.
    12. Debels, Dieter & De Reyck, Bert & Leus, Roel & Vanhoucke, Mario, 2006. "A hybrid scatter search/electromagnetism meta-heuristic for project scheduling," European Journal of Operational Research, Elsevier, vol. 169(2), pages 638-653, March.
    13. Weiqi Li, 2011. "Seeking global edges for traveling salesman problem in multi-start search," Journal of Global Optimization, Springer, vol. 51(3), pages 515-540, November.
    14. Gerald Senarclens de Grancy & Marc Reimann, 2016. "Vehicle routing problems with time windows and multiple service workers: a systematic comparison between ACO and GRASP," 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. 24(1), pages 29-48, March.
    15. Stefan Irnich & Daniel Villeneuve, 2006. "The Shortest-Path Problem with Resource Constraints and k -Cycle Elimination for k (ge) 3," INFORMS Journal on Computing, INFORMS, vol. 18(3), pages 391-406, August.
    16. Bo Liu & Ling Wang & Ying Liu & Shouyang Wang, 2011. "A unified framework for population-based metaheuristics," Annals of Operations Research, Springer, vol. 186(1), pages 231-262, June.
    17. N Wassan, 2007. "Reactive tabu adaptive memory programming search for the vehicle routing problem with backhauls," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(12), pages 1630-1641, December.
    18. Zvi Drezner & Peter Hahn & Éeric Taillard, 2005. "Recent Advances for the Quadratic Assignment Problem with Special Emphasis on Instances that are Difficult for Meta-Heuristic Methods," Annals of Operations Research, Springer, vol. 139(1), pages 65-94, October.
    19. Thiago Queiroz & Flávio Miyazawa, 2014. "Order and static stability into the strip packing problem," Annals of Operations Research, Springer, vol. 223(1), pages 137-154, December.
    20. Silva, Elsa & Alvelos, Filipe & Valério de Carvalho, J.M., 2010. "An integer programming model for two- and three-stage two-dimensional cutting stock problems," European Journal of Operational Research, Elsevier, vol. 205(3), pages 699-708, September.

    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:annopr:v:183:y:2011:i:1:p:143-161:10.1007/s10479-009-0545-0. 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.