IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v224y2013i1p65-78.html
   My bibliography  Save this article

The Capacitated Team Orienteering Problem: A Bi-level Filter-and-Fan method

Author

Listed:
  • Tarantilis, C.D.
  • Stavropoulou, F.
  • Repoussis, P.P.

Abstract

This paper focuses on vehicle routing problems with profits and addresses the so-called Capacitated Team Orienteering Problem. Given a set of customers with a priori known profits and demands, the objective is to find the subset of customers, for which the collected profit is maximized, and to determine the visiting sequence and assignment to vehicle routes assuming capacity and route duration restrictions. The proposed method adopts a hierarchical bi-level search framework that takes advantage of different search landscapes. At the upper level, the solution space is explored on the basis of the collected profit, using a Filter-and-Fan method and a combination of profit oriented neighborhoods, while at the lower level the routing of customers is optimized in terms of traveling distance via a Variable Neighborhood Descent method. Computational experiments on benchmark data sets illustrate the efficiency and effectiveness of the proposed approach. Compared to existing results, new upper bounds are produced with competitive computational times.

Suggested Citation

  • Tarantilis, C.D. & Stavropoulou, F. & Repoussis, P.P., 2013. "The Capacitated Team Orienteering Problem: A Bi-level Filter-and-Fan method," European Journal of Operational Research, Elsevier, vol. 224(1), pages 65-78.
  • Handle: RePEc:eee:ejores:v:224:y:2013:i:1:p:65-78
    DOI: 10.1016/j.ejor.2012.07.032
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221712005735
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejor.2012.07.032?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. Fred Glover, 1989. "Tabu Search---Part I," INFORMS Journal on Computing, INFORMS, vol. 1(3), pages 190-206, August.
    2. Christos D. Tarantilis & Emmanouil E. Zachariadis & Chris T. Kiranoudis, 2008. "A Hybrid Guided Local Search for the Vehicle-Routing Problem with Intermediate Replenishment Facilities," INFORMS Journal on Computing, INFORMS, vol. 20(1), pages 154-168, February.
    3. C Archetti & D Feillet & A Hertz & M G Speranza, 2009. "The capacitated team orienteering and profitable tour problems," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(6), pages 831-842, June.
    4. César Rego & Fred Glover, 2010. "Ejection chain and filter-and-fan methods in combinatorial optimization," Annals of Operations Research, Springer, vol. 175(1), pages 77-105, March.
    5. Dominique Feillet & Pierre Dejax & Michel Gendreau, 2005. "Traveling Salesman Problems with Profits," Transportation Science, INFORMS, vol. 39(2), pages 188-205, May.
    6. Gilbert Laporte, 2009. "Fifty Years of Vehicle Routing," Transportation Science, INFORMS, vol. 43(4), pages 408-416, November.
    7. Vansteenwegen, Pieter & Souffriau, Wouter & Oudheusden, Dirk Van, 2011. "The orienteering problem: A survey," European Journal of Operational Research, Elsevier, vol. 209(1), pages 1-10, February.
    8. Chao, I-Ming & Golden, Bruce L. & Wasil, Edward A., 1996. "The team orienteering problem," European Journal of Operational Research, Elsevier, vol. 88(3), pages 464-474, February.
    9. Olli Bräysy & Wout Dullaert & Geir Hasle & David Mester & Michel Gendreau, 2008. "An Effective Multirestart Deterministic Annealing Metaheuristic for the Fleet Size and Mix Vehicle-Routing Problem with Time Windows," Transportation Science, INFORMS, vol. 42(3), pages 371-386, 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. Asma Ben-Said & Racha El-Hajj & Aziz Moukrim, 2019. "A variable space search heuristic for the Capacitated Team Orienteering Problem," Journal of Heuristics, Springer, vol. 25(2), pages 273-303, April.
    2. Zhao, Yanlu & Alfandari, Laurent, 2020. "Design of diversified package tours for the digital travel industry : A branch-cut-and-price approach," European Journal of Operational Research, Elsevier, vol. 285(3), pages 825-843.
    3. Stavropoulou, F. & Repoussis, P.P. & Tarantilis, C.D., 2019. "The Vehicle Routing Problem with Profits and consistency constraints," European Journal of Operational Research, Elsevier, vol. 274(1), pages 340-356.
    4. Orlis, Christos & Laganá, Demetrio & Dullaert, Wout & Vigo, Daniele, 2020. "Distribution with Quality of Service Considerations: The Capacitated Routing Problem with Profits and Service Level Requirements," Omega, Elsevier, vol. 93(C).
    5. Kotiloglu, S. & Lappas, T. & Pelechrinis, K. & Repoussis, P.P., 2017. "Personalized multi-period tour recommendations," Tourism Management, Elsevier, vol. 62(C), pages 76-88.
    6. Gunawan, Aldy & Lau, Hoong Chuin & Vansteenwegen, Pieter, 2016. "Orienteering Problem: A survey of recent variants, solution approaches and applications," European Journal of Operational Research, Elsevier, vol. 255(2), pages 315-332.
    7. Bian, Zheyong & Liu, Xiang, 2018. "A real-time adjustment strategy for the operational level stochastic orienteering problem: A simulation-aided optimization approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 115(C), pages 246-266.

    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. Gunawan, Aldy & Lau, Hoong Chuin & Vansteenwegen, Pieter, 2016. "Orienteering Problem: A survey of recent variants, solution approaches and applications," European Journal of Operational Research, Elsevier, vol. 255(2), pages 315-332.
    2. Balcik, Burcu, 2017. "Site selection and vehicle routing for post-disaster rapid needs assessment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 101(C), pages 30-58.
    3. 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.
    4. Orlis, Christos & Laganá, Demetrio & Dullaert, Wout & Vigo, Daniele, 2020. "Distribution with Quality of Service Considerations: The Capacitated Routing Problem with Profits and Service Level Requirements," Omega, Elsevier, vol. 93(C).
    5. Freeman, Nickolas K. & Keskin, Burcu B. & Çapar, İbrahim, 2018. "Attractive orienteering problem with proximity and timing interactions," European Journal of Operational Research, Elsevier, vol. 266(1), pages 354-370.
    6. Jost, Christian & Jungwirth, Alexander & Kolisch, Rainer & Schiffels, Sebastian, 2022. "Consistent vehicle routing with pickup decisions - Insights from sport academy training transfers," European Journal of Operational Research, Elsevier, vol. 298(1), pages 337-350.
    7. Bian, Zheyong & Liu, Xiang, 2018. "A real-time adjustment strategy for the operational level stochastic orienteering problem: A simulation-aided optimization approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 115(C), pages 246-266.
    8. Şahinyazan, Feyza Güliz & Kara, Bahar Y. & Taner, Mehmet Rüştü, 2015. "Selective vehicle routing for a mobile blood donation system," European Journal of Operational Research, Elsevier, vol. 245(1), pages 22-34.
    9. Racha El-Hajj & Rym Nesrine Guibadj & Aziz Moukrim & Mehdi Serairi, 2020. "A PSO based algorithm with an efficient optimal split procedure for the multiperiod vehicle routing problem with profit," Annals of Operations Research, Springer, vol. 291(1), pages 281-316, August.
    10. Yu, Bin & Shan, Wenxuan & Sheu, Jiuh-Biing & Diabat, Ali, 2022. "Branch-and-price for a combined order selection and distribution problem in online community group-buying of perishable products," Transportation Research Part B: Methodological, Elsevier, vol. 158(C), pages 341-373.
    11. Archetti, Claudia & Corberán, Ángel & Plana, Isaac & Sanchis, José Maria & Speranza, M. Grazia, 2015. "A matheuristic for the Team Orienteering Arc Routing Problem," European Journal of Operational Research, Elsevier, vol. 245(2), pages 392-401.
    12. Afsaneh Amiri & Majid Salari, 2019. "Time-constrained maximal covering routing problem," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 41(2), pages 415-468, June.
    13. Stavropoulou, F. & Repoussis, P.P. & Tarantilis, C.D., 2019. "The Vehicle Routing Problem with Profits and consistency constraints," European Journal of Operational Research, Elsevier, vol. 274(1), pages 340-356.
    14. Ahmadi-Javid, Amir & Amiri, Elahe & Meskar, Mahla, 2018. "A Profit-Maximization Location-Routing-Pricing Problem: A Branch-and-Price Algorithm," European Journal of Operational Research, Elsevier, vol. 271(3), pages 866-881.
    15. Polyakovskiy, S. & Neumann, F., 2017. "The Packing While Traveling Problem," European Journal of Operational Research, Elsevier, vol. 258(2), pages 424-439.
    16. Rahma Lahyani & Mahdi Khemakhem & Frédéric Semet, 2017. "A unified matheuristic for solving multi-constrained traveling salesman problems with profits," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 5(3), pages 393-422, September.
    17. Álvarez-Miranda, Eduardo & Luipersbeck, Martin & Sinnl, Markus, 2018. "Gotta (efficiently) catch them all: Pokémon GO meets Orienteering Problems," European Journal of Operational Research, Elsevier, vol. 265(2), pages 779-794.
    18. Behrend, Moritz & Meisel, Frank & Fagerholt, Kjetil & Andersson, Henrik, 2021. "A multi-period analysis of the integrated item-sharing and crowdshipping problem," European Journal of Operational Research, Elsevier, vol. 292(2), pages 483-499.
    19. Oruc, Buse Eylul & Kara, Bahar Yetis, 2018. "Post-disaster assessment routing problem," Transportation Research Part B: Methodological, Elsevier, vol. 116(C), pages 76-102.
    20. Yu, Qinxiao & Fang, Kan & Zhu, Ning & Ma, Shoufeng, 2019. "A matheuristic approach to the orienteering problem with service time dependent profits," European Journal of Operational Research, Elsevier, vol. 273(2), pages 488-503.

    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:224:y:2013:i:1:p:65-78. 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.