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Planning the trip itinerary for tourist groups

Author

Listed:
  • Kadri Sylejmani

    (University of Prishtina)

  • Jürgen Dorn

    (Vienna University of Technology)

  • Nysret Musliu

    (Vienna University of Technology)

Abstract

Sightseeing trips are often done in groups, where tourists enjoy their trip in company with their relatives or friends. Therefore, in this paper, in order to model the case of trips for tourist groups, we introduce a new problem, as an extension of the existing problem in the literature that is used for planning the trip of a single tourist. The new problem extends the existing problem with two additional concepts. The first is the consideration of multiple tourists, where their individual preferences about points of interests are taken into account, and the second is the introduction of the concept of mutual social relationship between the different tourists. For the actual single tourist trip problem, we use an algorithm that obtains comparable results with the state of the art algorithms, whereas for the group trip problem, since no solution has been published before, we design a new algorithm based on tabu search metaheuristic that uses two new unique operators for exploring the search space. As a result, this paper proposes an anytime algorithm that in average takes about 20 s to obtain better personalized itineraries for tourist groups than when scheduling the whole group together.

Suggested Citation

  • Kadri Sylejmani & Jürgen Dorn & Nysret Musliu, 0. "Planning the trip itinerary for tourist groups," Information Technology & Tourism, Springer, vol. 0, pages 1-40.
    • Handle: RePEc:spr:infott:v::y::i::d:10.1007_s40558-017-0080-9
    DOI: 10.1007/s40558-017-0080-9
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    References listed on IDEAS

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    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. José Ruiz-Meza & Julio Brito & Jairo R. Montoya-Torres, 2021. "Multi-Objective Fuzzy Tourist Trip Design Problem with Heterogeneous Preferences and Sustainable Itineraries," Sustainability, MDPI, vol. 13(17), pages 1-22, August.
    2. Ernesto Tarantino & Ivanoe De Falco & Umberto Scafuri, 2019. "A mobile personalized tourist guide and its user evaluation," Information Technology & Tourism, Springer, vol. 21(3), pages 413-455, September.
    3. 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.
    4. Thuy Ngoc Nguyen & Francesco Ricci, 2018. "A chat-based group recommender system for tourism," Information Technology & Tourism, Springer, vol. 18(1), pages 5-28, April.
    5. Hoonseong Oh & Sangmin Lee, 2021. "Evaluation and Interpretation of Tourist Satisfaction for Local Korean Festivals Using Explainable AI," Sustainability, MDPI, vol. 13(19), pages 1-18, September.

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