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Metaheuristics for Tourist Trip Planning

In: Metaheuristics in the Service Industry

Author

Listed:
  • Pieter Vansteenwegen

    (Katholieke Universiteit Leuven)

  • Wouter Souffriau

    (Katholieke Universiteit Leuven)

  • Greet Vanden Berghe

    (Katholieke Universiteit Leuven)

  • Dirk Van Oudheusden

    (Katholieke Universiteit Leuven)

Abstract

The aim of this paper is to present an overview of metaheuristics used in tourism and to introduce Skewed VNS to solve the team orienteering problem (TOP). Selecting the most interesting points of interest and designing a personalised tourist trip, can be modelled as a TOP with time windows (TOPTW). Guided local search (GLS) and variable neighbourhood search (VNS) are applied to efficiently solve the TOP. Iterated local search (ILS) is implemented to solve the TOPTW. The GLS and VNS algorithms are compared with the best known heuristics and applied on large problem sets. The obtained results are almost of the same quality as the results of these heuristics but the computational time is reduced significantly. For some of the problems VNS calculates new best solutions. The results of the ILS algorithm, applied to large problem sets, have an average gap with the optimal solution of only 2.7%, with much less computational effort.

Suggested Citation

  • Pieter Vansteenwegen & Wouter Souffriau & Greet Vanden Berghe & Dirk Van Oudheusden, 2009. "Metaheuristics for Tourist Trip Planning," Lecture Notes in Economics and Mathematical Systems, in: Kenneth Sörensen & Marc Sevaux & Walter Habenicht & Martin Josef Geiger (ed.), Metaheuristics in the Service Industry, chapter 2, pages 15-31, Springer.
    • Handle: RePEc:spr:lnechp:978-3-642-00939-6_2
    DOI: 10.1007/978-3-642-00939-6_2
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    Citations

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    Cited by:

    1. 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.
    2. Shahmanzari, Masoud & Mansini, Renata, 2024. "A learning-based granular variable neighborhood search for a multi-period election logistics problem with time-dependent profits," European Journal of Operational Research, Elsevier, vol. 319(1), pages 135-152.
    3. 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.
    4. Labadie, Nacima & Mansini, Renata & Melechovský, Jan & Wolfler Calvo, Roberto, 2012. "The Team Orienteering Problem with Time Windows: An LP-based Granular Variable Neighborhood Search," European Journal of Operational Research, Elsevier, vol. 220(1), pages 15-27.
    5. Verbeeck, C. & Vansteenwegen, P. & Aghezzaf, E.-H., 2016. "Solving the stochastic time-dependent orienteering problem with time windows," European Journal of Operational Research, Elsevier, vol. 255(3), pages 699-718.
    6. Morteza Keshtkaran & Koorush Ziarati, 2016. "A novel GRASP solution approach for the Orienteering Problem," Journal of Heuristics, Springer, vol. 22(5), pages 699-726, October.
    7. Morteza Keshtkaran & Koorush Ziarati & Andrea Bettinelli & Daniele Vigo, 2016. "Enhanced exact solution methods for the Team Orienteering Problem," International Journal of Production Research, Taylor & Francis Journals, vol. 54(2), pages 591-601, January.
    8. Vidal, Thibaut & Laporte, Gilbert & Matl, Piotr, 2020. "A concise guide to existing and emerging vehicle routing problem variants," European Journal of Operational Research, Elsevier, vol. 286(2), pages 401-416.
    9. Thibaut Vidal & Nelson Maculan & Luiz Satoru Ochi & Puca Huachi Vaz Penna, 2016. "Large Neighborhoods with Implicit Customer Selection for Vehicle Routing Problems with Profits," Transportation Science, INFORMS, vol. 50(2), pages 720-734, May.
    10. José Ruiz-Meza & Jairo R. Montoya-Torres, 2021. "Tourist trip design with heterogeneous preferences, transport mode selection and environmental considerations," Annals of Operations Research, Springer, vol. 305(1), pages 227-249, October.
    11. Yücel, E. & Salman, F.S. & Gel, E.S. & Örmeci, E.L. & Gel, A., 2013. "Optimizing specimen collection for processing in clinical testing laboratories," European Journal of Operational Research, Elsevier, vol. 227(3), pages 503-514.
    12. 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).
    13. 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.

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