IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v237y2014i1p29-49.html
   My bibliography  Save this article

A memetic algorithm for the orienteering problem with hotel selection

Author

Listed:
  • Divsalar, A.
  • Vansteenwegen, P.
  • Sörensen, K.
  • Cattrysse, D.

Abstract

In this paper, a memetic algorithm is developed to solve the orienteering problem with hotel selection (OPHS). The algorithm consists of two levels: a genetic component mainly focuses on finding a good sequence of intermediate hotels, whereas six local search moves embedded in a variable neighborhood structure deal with the selection and sequencing of vertices between the hotels. A set of 176 new and larger benchmark instances of OPHS are created based on optimal solutions of regular orienteering problems. Our algorithm is applied on these new instances as well as on 224 benchmark instances from the literature. The results are compared with the known optimal solutions and with the only other existing algorithm for this problem. The results clearly show that our memetic algorithm outperforms the existing algorithm in terms of solution quality and computational time. A sensitivity analysis shows the significant impact of the number of possible sequences of hotels on the difficulty of an OPHS instance.

Suggested Citation

  • Divsalar, A. & Vansteenwegen, P. & Sörensen, K. & Cattrysse, D., 2014. "A memetic algorithm for the orienteering problem with hotel selection," European Journal of Operational Research, Elsevier, vol. 237(1), pages 29-49.
  • Handle: RePEc:eee:ejores:v:237:y:2014:i:1:p:29-49
    DOI: 10.1016/j.ejor.2014.01.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221714000034
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejor.2014.01.001?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. Dang, Duc-Cuong & Guibadj, Rym Nesrine & Moukrim, Aziz, 2013. "An effective PSO-inspired algorithm for the team orienteering problem," European Journal of Operational Research, Elsevier, vol. 229(2), pages 332-344.
    2. Beasley, JE, 1983. "Route first--Cluster second methods for vehicle routing," Omega, Elsevier, vol. 11(4), pages 403-408.
    3. 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.
    4. Boudia, M. & Prins, C., 2009. "A memetic algorithm with dynamic population management for an integrated production-distribution problem," European Journal of Operational Research, Elsevier, vol. 195(3), pages 703-715, June.
    5. Angelelli, Enrico & Grazia Speranza, Maria, 2002. "The periodic vehicle routing problem with intermediate facilities," European Journal of Operational Research, Elsevier, vol. 137(2), pages 233-247, March.
    6. P Vansteenwegen & W Souffriau & K Sörensen, 2012. "The travelling salesperson problem with hotel selection," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 63(2), pages 207-217, February.
    7. Crevier, Benoit & Cordeau, Jean-Francois & Laporte, Gilbert, 2007. "The multi-depot vehicle routing problem with inter-depot routes," European Journal of Operational Research, Elsevier, vol. 176(2), pages 756-773, January.
    8. E Angelelli & M G Speranza, 2002. "The application of a vehicle routing model to a waste-collection problem: two case studies," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(9), pages 944-952, September.
    9. Marius M. Solomon, 1987. "Algorithms for the Vehicle Routing and Scheduling Problems with Time Window Constraints," Operations Research, INFORMS, vol. 35(2), pages 254-265, April.
    10. Bruce L. Golden & Larry Levy & Rakesh Vohra, 1987. "The orienteering problem," Naval Research Logistics (NRL), John Wiley & Sons, vol. 34(3), pages 307-318, June.
    11. Divsalar, A. & Vansteenwegen, P. & Cattrysse, D., 2013. "A variable neighborhood search method for the orienteering problem with hotel selection," International Journal of Production Economics, Elsevier, vol. 145(1), pages 150-160.
    12. 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.
    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. Dewil, R. & Vansteenwegen, P. & Cattrysse, D. & Van Oudheusden, D., 2015. "A minimum cost network flow model for the maximum covering and patrol routing problem," European Journal of Operational Research, Elsevier, vol. 247(1), pages 27-36.
    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. Lin, Jun & Qian, Yanjun & Cui, Wentian & Goh, Thong Ngee, 2015. "An effective approach for scheduling coupled activities in development projects," European Journal of Operational Research, Elsevier, vol. 243(1), pages 97-108.
    4. Zhou, Yangming & Wang, Gezi & Hao, Jin-Kao & Geng, Na & Jiang, Zhibin, 2023. "A fast tri-individual memetic search approach for the distance-based critical node problem," European Journal of Operational Research, Elsevier, vol. 308(2), pages 540-554.
    5. Sohrabi, Somayeh & Ziarati, Koorush & Keshtkaran, Morteza, 2020. "A Greedy Randomized Adaptive Search Procedure for the Orienteering Problem with Hotel Selection," European Journal of Operational Research, Elsevier, vol. 283(2), pages 426-440.
    6. Ruiz-Meza, José & Montoya-Torres, Jairo R., 2022. "A systematic literature review for the tourist trip design problem: Extensions, solution techniques and future research lines," Operations Research Perspectives, Elsevier, vol. 9(C).
    7. Kotiloglu, S. & Lappas, T. & Pelechrinis, K. & Repoussis, P.P., 2017. "Personalized multi-period tour recommendations," Tourism Management, Elsevier, vol. 62(C), pages 76-88.
    8. CASTRO, Marco & SÖRENSEN, Kenneth & GOOS, Peter & VANSTEENWEGEN, Pieter, 2014. "The multiple travelling salesperson problem with hotel selection," Working Papers 2014030, University of Antwerp, Faculty of Business and Economics.
    9. Maximilian Schiffer & Grit Walther, 2018. "An Adaptive Large Neighborhood Search for the Location-routing Problem with Intra-route Facilities," Transportation Science, INFORMS, vol. 52(2), pages 331-352, March.
    10. 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.
    11. Schiffer, Maximilian & Schneider, Michael & Laporte, Gilbert, 2018. "Designing sustainable mid-haul logistics networks with intra-route multi-resource facilities," European Journal of Operational Research, Elsevier, vol. 265(2), pages 517-532.
    12. Du, Jiaoman & Zhou, Jiandong & Li, Xiang & Li, Lei & Guo, Ao, 2021. "Integrated self-driving travel scheme planning," International Journal of Production Economics, Elsevier, vol. 232(C).

    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. Sohrabi, Somayeh & Ziarati, Koorush & Keshtkaran, Morteza, 2020. "A Greedy Randomized Adaptive Search Procedure for the Orienteering Problem with Hotel Selection," European Journal of Operational Research, Elsevier, vol. 283(2), pages 426-440.
    2. Maximilian Schiffer & Michael Schneider & Grit Walther & Gilbert Laporte, 2019. "Vehicle Routing and Location Routing with Intermediate Stops: A Review," Transportation Science, INFORMS, vol. 53(2), pages 319-343, March.
    3. Markov, Iliya & Varone, Sacha & Bierlaire, Michel, 2016. "Integrating a heterogeneous fixed fleet and a flexible assignment of destination depots in the waste collection VRP with intermediate facilities," Transportation Research Part B: Methodological, Elsevier, vol. 84(C), pages 256-273.
    4. 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.
    5. 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.
    6. Du, Jiaoman & Zhou, Jiandong & Li, Xiang & Li, Lei & Guo, Ao, 2021. "Integrated self-driving travel scheme planning," International Journal of Production Economics, Elsevier, vol. 232(C).
    7. Schneider, M. & Stenger, A. & Hof, J., 2015. "An Adaptive VNS Algorithm for Vehicle Routing Problems with Intermediate Stops," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 63500, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    8. Dang, Duc-Cuong & Guibadj, Rym Nesrine & Moukrim, Aziz, 2013. "An effective PSO-inspired algorithm for the team orienteering problem," European Journal of Operational Research, Elsevier, vol. 229(2), pages 332-344.
    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. Ruiz-Meza, José & Montoya-Torres, Jairo R., 2022. "A systematic literature review for the tourist trip design problem: Extensions, solution techniques and future research lines," Operations Research Perspectives, Elsevier, vol. 9(C).
    11. 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.
    12. 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.
    13. Ramos, Tânia Rodrigues Pereira & Gomes, Maria Isabel & Barbosa-Póvoa, Ana Paula, 2014. "Planning a sustainable reverse logistics system: Balancing costs with environmental and social concerns," Omega, Elsevier, vol. 48(C), pages 60-74.
    14. Erfan Ghorbani & Mahdi Alinaghian & Gevork. B. Gharehpetian & Sajad Mohammadi & Guido Perboli, 2020. "A Survey on Environmentally Friendly Vehicle Routing Problem and a Proposal of Its Classification," Sustainability, MDPI, vol. 12(21), pages 1-71, October.
    15. 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.
    16. Christos Orlis & Nicola Bianchessi & Roberto Roberti & Wout Dullaert, 2020. "The Team Orienteering Problem with Overlaps: An Application in Cash Logistics," Transportation Science, INFORMS, vol. 54(2), pages 470-487, March.
    17. Tânia Rodrigues Pereira Ramos & Maria Isabel Gomes & Ana Paula Barbosa-Póvoa, 2020. "A new matheuristic approach for the multi-depot vehicle routing problem with inter-depot routes," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(1), pages 75-110, March.
    18. Aldy Gunawan & Hoong Chuin Lau & Pieter Vansteenwegen & Kun Lu, 2017. "Well-tuned algorithms for the Team Orienteering Problem with Time Windows," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(8), pages 861-876, August.
    19. Maximilian Schiffer & Grit Walther, 2018. "An Adaptive Large Neighborhood Search for the Location-routing Problem with Intra-route Facilities," Transportation Science, INFORMS, vol. 52(2), pages 331-352, March.
    20. Hu, Qian & Lim, Andrew, 2014. "An iterative three-component heuristic for the team orienteering problem with time windows," European Journal of Operational Research, Elsevier, vol. 232(2), pages 276-286.

    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:237:y:2014:i:1:p:29-49. 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.