IDEAS home Printed from https://ideas.repec.org/a/eee/soceps/v101y2025ics0038012125001351.html

Tourist trip planning with priority discipline

Author

Listed:
  • Hu, Yuning
  • Luo, Xinggang
  • Liu, Xinrui
  • Ji, Pengli
  • Zhang, Zhongliang

Abstract

In recent years, the tourism industry has experienced robust growth and plays a crucial role in the economy. Tourist congestion is a common issue that can significantly affect service quality. To maintain a high level of service in congested environments, many attractions offer priority services, such as the VIP services commonly offered in malls or amusement parks, which grant priority access to specific customers and allow them to reduce or even eliminate waiting times. By integrating such priority discipline, businesses can enhance the satisfaction of high-priority tourists while improving profitability. In this paper, a new tourist trip design problem that incorporates two priority discipline strategies is introduced, for the first time representing the priority discipline as constraints within the model to ensure that the solutions strictly adhere to the discipline. To address this problem, a branch-and-bound algorithm is proposed for solving small-scale instances, and an adaptive large neighborhood search algorithm is developed to efficiently handle large-scale instances, with a customized heuristic rule used to determine the visiting orders at each attraction. The effectiveness of both algorithms is demonstrated through experimental results. Finally, parameter analysis is conducted for the model, and several managerial insights are obtained.

Suggested Citation

  • Hu, Yuning & Luo, Xinggang & Liu, Xinrui & Ji, Pengli & Zhang, Zhongliang, 2025. "Tourist trip planning with priority discipline," Socio-Economic Planning Sciences, Elsevier, vol. 101(C).
  • Handle: RePEc:eee:soceps:v:101:y:2025:i:c:s0038012125001351
    DOI: 10.1016/j.seps.2025.102286
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0038012125001351
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.seps.2025.102286?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Na Li & Xiaorui Li & Paul Forero, 2022. "Physician scheduling for outpatient department with nonhomogeneous patient arrival and priority queue," Flexible Services and Manufacturing Journal, Springer, vol. 34(4), pages 879-915, December.
    2. David Pisinger & Stefan Ropke, 2019. "Large Neighborhood Search," International Series in Operations Research & Management Science, in: Michel Gendreau & Jean-Yves Potvin (ed.), Handbook of Metaheuristics, edition 3, chapter 0, pages 99-127, Springer.
    3. Trigos, Federico & Vazquez, Alan R. & Cárdenas-Barrón, Leopoldo Eduardo, 2019. "A simulation-based heuristic that promotes business profit while increasing the perceived quality of service industries," International Journal of Production Economics, Elsevier, vol. 211(C), pages 60-70.
    4. Jengchung Victor Chen & Hsing Kenneth Cheng & Hui-Ju Veronica Hsiao, 2016. "Loyalty and Profitability of VIP and Non-VIP Customers in the Banking Service Industry," Service Science, INFORMS, vol. 8(1), pages 19-36, March.
    5. M. Arslan Ornek & Cemalettin Ozturk & Ipek Sugut, 2022. "Integer and constraint programming model formulations for flight-gate assignment problem," Operational Research, Springer, vol. 22(1), pages 135-163, March.
    6. Brent Johnson & Limin Peng, 2008. "Rank-based variable selection," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 20(3), pages 241-252.
    7. Stefan Ropke & David Pisinger, 2006. "An Adaptive Large Neighborhood Search Heuristic for the Pickup and Delivery Problem with Time Windows," Transportation Science, INFORMS, vol. 40(4), pages 455-472, November.
    8. Zhang, Shu & Ohlmann, Jeffrey W. & Thomas, Barrett W., 2020. "Multi-period orienteering with uncertain adoption likelihood and waiting at customers," European Journal of Operational Research, Elsevier, vol. 282(1), pages 288-303.
    9. Kang, Myunghwa & Gretzel, Ulrike, 2012. "Effects of podcast tours on tourist experiences in a national park," Tourism Management, Elsevier, vol. 33(2), pages 440-455.
    10. Shu Zhang & Jeffrey W. Ohlmann & Barrett W. Thomas, 2018. "Dynamic Orienteering on a Network of Queues," Transportation Science, INFORMS, vol. 52(3), pages 691-706, June.
    11. 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).
    12. Zhang, Shu & Ohlmann, Jeffrey W. & Thomas, Barrett W., 2014. "A priori orienteering with time windows and stochastic wait times at customers," European Journal of Operational Research, Elsevier, vol. 239(1), pages 70-79.
    13. 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.
    14. 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.
    Full references (including those not matched with items on IDEAS)

    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. 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).
    2. Gulcin Dinc Yalcin & Hilal Malta & Seher Saylik, 2023. "A new mathematical model and a heuristic algorithm for the tourist trip design problem under new constraints: a real-world application," OPSEARCH, Springer;Operational Research Society of India, vol. 60(4), pages 1703-1730, December.
    3. Shiri, Davood & Akbari, Vahid & Hassanzadeh, Ali, 2024. "The Capacitated Team Orienteering Problem: An online optimization framework with predictions of unknown accuracy," Transportation Research Part B: Methodological, Elsevier, vol. 185(C).
    4. 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.
    5. Zhang, Shu & Ohlmann, Jeffrey W. & Thomas, Barrett W., 2020. "Multi-period orienteering with uncertain adoption likelihood and waiting at customers," European Journal of Operational Research, Elsevier, vol. 282(1), pages 288-303.
    6. Qinxiao Yu & Chun Cheng & Ning Zhu, 2022. "Robust Team Orienteering Problem with Decreasing Profits," INFORMS Journal on Computing, INFORMS, vol. 34(6), pages 3215-3233, November.
    7. Baals, Julian & Emde, Simon & Turkensteen, Marcel, 2023. "Minimizing earliness-tardiness costs in supplier networks—A just-in-time truck routing problem," European Journal of Operational Research, Elsevier, vol. 306(2), pages 707-741.
    8. Kallestad, Jakob & Hasibi, Ramin & Hemmati, Ahmad & Sörensen, Kenneth, 2023. "A general deep reinforcement learning hyperheuristic framework for solving combinatorial optimization problems," European Journal of Operational Research, Elsevier, vol. 309(1), pages 446-468.
    9. John E. Fontecha & Oscar O. Guaje & Daniel Duque & Raha Akhavan-Tabatabaei & Juan P. Rodríguez & Andrés L. Medaglia, 2020. "Combined maintenance and routing optimization for large-scale sewage cleaning," Annals of Operations Research, Springer, vol. 286(1), pages 441-474, March.
    10. Dumez, Dorian & Lehuédé, Fabien & Péton, Olivier, 2021. "A large neighborhood search approach to the vehicle routing problem with delivery options," Transportation Research Part B: Methodological, Elsevier, vol. 144(C), pages 103-132.
    11. Singh, Nitish & Dang, Quang-Vinh & Akcay, Alp & Adan, Ivo & Martagan, Tugce, 2022. "A matheuristic for AGV scheduling with battery constraints," European Journal of Operational Research, Elsevier, vol. 298(3), pages 855-873.
    12. Moradi, Nima & Mafakheri, Fereshteh & Wang, Chun & Baldacci, Roberto, 2026. "Robot-aided electric vehicle routing problem with lockers and prime customers prioritization," European Journal of Operational Research, Elsevier, vol. 328(3), pages 1018-1035.
    13. Frey, Christian M.M. & Jungwirth, Alexander & Frey, Markus & Kolisch, Rainer, 2023. "The vehicle routing problem with time windows and flexible delivery locations," European Journal of Operational Research, Elsevier, vol. 308(3), pages 1142-1159.
    14. Lei He & Mathijs Weerdt & Neil Yorke-Smith, 2020. "Time/sequence-dependent scheduling: the design and evaluation of a general purpose tabu-based adaptive large neighbourhood search algorithm," Journal of Intelligent Manufacturing, Springer, vol. 31(4), pages 1051-1078, April.
    15. Canca, David & De-Los-Santos, Alicia & Laporte, Gilbert & Mesa, Juan A., 2019. "Integrated Railway Rapid Transit Network Design and Line Planning problem with maximum profit," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 127(C), pages 1-30.
    16. 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.
    17. Ozyavas, Pinar & Ursavas, Evrim & Buijs, Paul & Teunter, Ruud, 2025. "Integrating shift planning and pick-up and delivery problems under limited courier availability," European Journal of Operational Research, Elsevier, vol. 326(2), pages 343-356.
    18. Yu, Vincent F. & Anh, Pham Tuan & Baldacci, Roberto, 2023. "A robust optimization approach for the vehicle routing problem with cross-docking under demand uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 173(C).
    19. Perumal, S.S.G. & Dollevoet, T.A.B. & Huisman, D. & Lusby, R.M. & Larsen, J. & Riis, M., 2020. "Solution Approaches for Vehicle and Crew Scheduling with Electric Buses," Econometric Institute Research Papers EI-2020-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    20. Jiang, Yupeng & Hu, Wei & Gu, Wenjuan & Yu, Yongguang & Xu, Meng, 2025. "A multi-mode hybrid electric vehicle routing problem with time windows," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 195(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:soceps:v:101:y:2025:i:c:s0038012125001351. 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/seps .

    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.