Skip to main content
SpringerLink
Log in

A new mathematical model and a heuristic algorithm for the tourist trip design problem under new constraints: a real-world application

  • Application Article
  • Published:
OPSEARCH Aims and scope Submit manuscript

Abstract

The tourist trip design problem (TTDP) is about to generate routes for tourists to maximize the points of interest (POIs) visited within specific time windows. In this study, new constraints: budget, weather and break are considered. First, the budget is required for entrance fees and the distance between two points where a taxi has to be used. Additionally, the expense of the break was taken into account. Then, the weather was considered for summer and for other seasons. On a summer day, tourists are likely to prefer visiting POIs, which are indoor areas, between specific times e.g. 11 a.m. to 3 p.m. to protect against the side effects of the sun. Furthermore, tourists need to take a break to relax during the trip. A mathematical model of the TTDP with these new constraints (TTDP-BWB) was developed. Then, a heuristic algorithm was developed with a new defined function that took the new constraints into account. The algorithm was codded using Android Studio and developed a mobile application for the case of Eskisehir in Türkiye. Problems are generated on the small and medium scale for the case of Eskisehir and used large-scale problems from published literature. The results of the algorithm were compared with the results of the mathematical model for the small scale problems. Additional, large-scale problems from literature were solved to see the performance of the heuristic algorithm. Computational results showed that the algorithm is promising.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

Notes

  1. Details of the all parameters are shown in https://docs.google.com/spreadsheets/d/1Hr08j6yttG9lYDaZ4u_1foFe0zYM6BUj/edit?usp=sharing&ouid=117375956105700927487&rtpof=true&sd=true. Note that new problems for the case of Eskisehir may be generated using this form.

  2. Details of the problem are shown in. https://drive.google.com/file/d/1PhQPGgbVnEsZs8KsTDVb5eBjHQ0FkmVk/view?usp=sharing

  3. All data are shown in https://drive.google.com/drive/folders/1fCUI2cz6nEgY1v7evBU32caZK4TiCkQG?usp=sharing

References

  1. Abbaspour, R., Samadzadegan, F.: Time-dependent personal tour planning and scheduling in metropolises. Expert Syst. Appl. 38(10), 12439–12452 (2011)

    Article  Google Scholar 

  2. Archetti, C., Herts, A., Speranza, M.G.: Metaheuristics for the team orienteering problem. J. Heuristics 13(1), 49–76 (2007)

    Article  Google Scholar 

  3. Archetti, C., Speranza, M.G., Corberán, Á., Sanchis, J.M., Plana, I.: The team orienteering arc routing problem. Transp. Sci. 48(3), 442–457 (2013)

    Article  Google Scholar 

  4. Archetti, C., Corberán, Á., Plana, I., Sanchis, J.M., Speranza, M.G.: A matheuristic for the team orienteering arc routing problem. Eur. J. Oper. Res. 245(2), 392–401 (2015)

    Article  Google Scholar 

  5. Brito, J., Expíósito-Márquez, A., Moreno, J.A.: A fuzzy GRASP algorithm for solving a tourist trip tesign problem. 2017 IEEE international conference on fuzzy systems (FUZZ IEEE), Naples, pp. 1–6. (2017)

  6. Bouly, H., Dang, D., Moukrim, A.: A memetic algorithm for team orienteering problems. 4OR, 8, 49-70 (2010)

  7. Boussier, S., Feiller, D., Gendreau, M.: An exact algorithm for team orienteering problems. 4OR, 5(3), 211–230 (2007)

  8. Chao, I., Golden, B., Wasil, E.: The team orienteering problem. Eur. J. Oper. Res. 88(3), 464–474 (1996)

    Article  Google Scholar 

  9. Chao, I., Golden, B., Wasil, E.: A fast and effective heuristic for the orienteering problem. Eur. J. Oper. Res. 88(3), 475–489 (1996)

    Article  Google Scholar 

  10. Dang, D.-C., Guibadj, R.N., Moukrim, A.: An effective PSO-inspired algorithm for the team orienteering problem. Eur. J. Oper. Res. 229, 332–344 (2013)

    Article  Google Scholar 

  11. Expósito, A., Mancini, S., Brito, J., Moreno, J.: A fuzzy GRASP for the tourist trip design with clustered POIs. Expert Syst. Appl. 127, 210–227 (2019)

    Article  Google Scholar 

  12. Garcia, A., Vansteenwegen, P., Arbelaitz, O., Souffriau, W., Linaza, M.T.: Integrating public transportation in personalised electronic tourist guides. Comput. Oper. Res. 40(3), 758–774 (2013)

    Article  Google Scholar 

  13. Gavalas, D., Kenteris, M., Konstantopoulos, C., Pantziou, G.: Web application for recommending personalised mobile tourist routes. IET Softw. 6(4), 313–322 (2012)

    Article  Google Scholar 

  14. Gavalas, D., Konstantopoulos, C., Mastakas, K., Pantziou, G.: A survey on algorithmic approaches for solving trip design problems. J. Heuristics 20, 291–328 (2014)

    Article  Google Scholar 

  15. Gavalas, D., Konstantopoulos, C., Mastakas, K., Pantziou, G., Vathis, N.: Heuristics for the time dependent team orienteering problem: an application to tourist route planning. Comput. Oper. Res. 62, 36–50 (2015)

    Article  Google Scholar 

  16. Godart, J.-M.: Combinatorial optimization based decision support system for trip planning. In information and communication technologies in tourism 1999, 318–327, Springer (1999)

  17. Gunawan, A., Lau, H.C., Vanteenwegen, P.: Orientering problem: a survey of recent variants, solution approaches and applications. Eur. J. Oper. Res. 255(2), 315–332 (2016)

    Article  Google Scholar 

  18. Hu, Q., Lim, A.: An iterative three-component heuristic for the team orienteering problem with time windows. Eur. J. Oper. Res. 232(2), 276–286 (2014)

    Article  Google Scholar 

  19. Keshtkaran, M., Ziarati, K., Bettinelli, A., Vigo, D.: Enhanced exact solution methods for the team orienteering problem. Int. J. Prod. Res. 54(2), 591–601 (2016)

    Article  Google Scholar 

  20. Ko, T., Qureshi, A.G., Schmöcker, J.-D., Fujı, S.: Tourist trip design problem considering fatigue. J. Eastern Asia Soc. Transp. Stud. 13, 1233–1248 (2019)

    Google Scholar 

  21. Kotiloglu, S., Lappas, T., Pelechrinis, K., Repoussis, P.: Personalized multi-period tour recommendations. Tour. Manag. 62, 76–88 (2017)

    Article  Google Scholar 

  22. Kronqvist, J., Bernal, D.E., Lundell, A., Grossmann, I.E.: A revive and comparison of solvers for convex MINLP. Optim. Eng. 20, 397–455 (2019)

    Article  Google Scholar 

  23. Labadie, N., Mansini, R., Calvo, W.R., Melechovský, J.: The team orienteering problem with time windows: an lp-based granular variable neighborhood search. Eur. J. Oper. Res. 220(1), 15–27 (2012)

    Article  Google Scholar 

  24. Laporte, G., Martello, S.: The selective travelling salesman problem. Discret. Appl. Math. 26, 193–207 (1990)

    Article  Google Scholar 

  25. Lin, S.-W., Vincent, F.Y.: A simulated annealing heuristic for the team orienteering problem with time windows. Eur. J. Oper. Res. 217(1), 94–107 (2012)

    Article  Google Scholar 

  26. Mei, Y.: Study on the application and improvement of ant colony algorithm in terminal tour route planning under Android platform. J. Intell. Fuzzy Syst. 35(3), 2761–2768 (2018)

    Article  Google Scholar 

  27. Montemanni, R., Gambardella, L.: An ant colony system for team orienteering problem with time windows. Found. Comput. Decis. Sci. 34(4), 287–306 (2009)

    Google Scholar 

  28. Muthuswamy, S., Lam, S.: Discreate particle swarm optimization for the team orienteering problem. Memet. Comput. 3, 287–303 (2011)

    Article  Google Scholar 

  29. Riera-Ladesma, J., Salazar-Gonzáles, J.J.: Solving the team orienteering arch routing problem with a column generation approach. Eur. J. Oper. Res. 262(1), 14–27 (2017)

    Article  Google Scholar 

  30. Ruiz-Meza, J., Montoya-Torres, J.R.: Tourist trip design with heterogeneous preferences, transport mode selection and environmental considerations. Ann. Oper. Res. 305(1), 227–249 (2021)

    Article  Google Scholar 

  31. Ruiz-Meza, J., Montoya-Torres, J.R.: A systematic literature review for the tourist trip design problem: extensions, solution techniques and future research lines. Oper. Res. Perspect. 9, 100228 (2022)

    Google Scholar 

  32. Souffriau, W., Vansteenwegen, P., Vertommen, J., Vanden Berghe, G., Van Oudheusden, D.: A personalized tourist trip design algorithm for mobile tourist guides. Appl. Artif. Intell. 22(10), 964–985 (2008)

    Article  Google Scholar 

  33. Souffriau, W., Maervoet, J., Vansteenwegen, P., Vanden Berghe, G., Van Oudheusden, D.: A mobile tourist decision support system for small footprint devices. In Bio-Inspired Systems: Computational and Ambient Intelligence. In: Proceedings of 10th international work-conference on artificial neural networks (IWANN2009), Special session on advances in AI models adaptable to mobile devices, number 5517 in Lecture Notes in Computer Science (pp. 1248–1255), Salamanca, Spain. ISBN 978–3–642–02477–1 (2009)

  34. Suarez, A.N., KoelenLacay, J., Villanueva, V., Ashley Velasquez, R., Reyes, C., Serrano, V., Borbon, C.D.: Impacts of coffee shop business to tourism industry in three cities of Batangas, Philippines. J. Tour. Hosp. Res. 14(1), 131–145 (2017)

    Google Scholar 

  35. Sylejmani, K., Dorn, J., Musliu, N.: Planning the trip itinerary for tourist groups. Inform. Technol. Tour. 17(3), 275–314 (2017)

    Article  Google Scholar 

  36. Tang, H., Miller-Hooks, E.: A tabu search heuristic for the team orienteering problem. Comput. Oper. Res. 32(6), 1379–1407 (2005)

    Article  Google Scholar 

  37. Vansteenwegen, P., Van Oudheusden, D.: The mobile tourist guide: An OR opportunity. OR Insight 20, 21–27 (2007)

    Article  Google Scholar 

  38. Vansteenwegen, P., Souffriau, W., Vanden Berghe, G., Van Oudheusden, D.: A guided local search metaheuristic for the team orienteering problem. Eur. J. Oper. Res. 196(1), 118–127 (2009)

    Article  Google Scholar 

  39. Vansteenwegen, P., Souffriau, W., Vanden Berghe, G., Van Oudheusden, D.: Iterated local search for the team orienteering problem with time windows. Comput. Oper. Res. 36(12), 3281–3290 (2009)

    Article  Google Scholar 

  40. Vansteenwegen, P., Souffriau, W., Vanden Berghe, G., Van Oudheusden, D.: Metaheuristics for tourist trip planning. Chapter in lecture notes in economics and mathematical systems, May. (2009c)

  41. Vansteenwegen, P., Souffriau, W., Van Oudheusden, D.: The orienteering problem: a survey. Eur. J. Oper. Res. 209, 1–10 (2011)

    Article  Google Scholar 

  42. Vansteenwegen, P., Souffriau, W., Vanden Berghe, G., Van Oudheusden, D.: The city trip planner: an expert system for tourist. Expert Syst. Appl. 38, 6540–6546 (2011)

    Article  Google Scholar 

  43. Zheng, W., Liao, Z., Qin, J.: Using a four-step heuristic algorithm to design personalized day tour route within a tourist attraction. Tour. Manag. 62, 335–349 (2017)

    Article  Google Scholar 

  44. Zheng, W., Ji, H., Lin, C., Wang, W., Yu, B.: Using a heuristic approach to design personalized urban tourism itineraries with hotel selection. Tour. Manag. 76(1), 1–14 (2020)

    Google Scholar 

  45. Zhao, Y., Alfandari, L.: Design of diversified package tours for the digital travel industry: a branch-cut-and-price approach. Eur. J. Oper. Res. 285(3), 825–843 (2020)

    Article  Google Scholar 

  46. W. T. Organization, Ed., UNWTO Tourism Highlights. (2020)

  47. Wörndl, W., Hefele, A., Herzog, D.: Recommending a sequence of interesting places for tourist trips. Inform. Technol. Tour. 17(1), 31–54 (2017)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Industrial Engineering, Faculty of Engineering, Eskisehir Technical University, Iki Eylul Campus, 26555, Eskisehir, Turkey

    Gulcin Dinc Yalcin, Hilal Malta & Seher Saylik

Authors
  1. Gulcin Dinc Yalcin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hilal Malta
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Seher Saylik
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Gulcin Dinc Yalcin.

Ethics declarations

Conflict of interest

The authors have submitted this work to the OPSEARCH for review and publication with full consent. The authors declare that they have no competing interests and have not been supported by any funding source. Also, all datasets used in this paper are available. The sources of data are given as footnote in the sections.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yalcin, G.D., Malta, H. & Saylik, S. A new mathematical model and a heuristic algorithm for the tourist trip design problem under new constraints: a real-world application. OPSEARCH 60, 1703–1730 (2023). https://doi.org/10.1007/s12597-023-00678-5

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12597-023-00678-5

Keywords

JEL Classification

Search

Navigation