Annals of Operations Research

, Volume 192, Issue 1, pp 67–86 | Cite as

On the tour planning problem

  • Chenbo Zhu
  • J. Q. Hu
  • Fengchun Wang
  • Yifan Xu
  • Rongzeng Cao
Article

Abstract

Increasingly, tourists are planning trips by themselves using the vast amount of information available on the Web. However, they still expect and want trip plan advisory services. In this paper, we study the tour planning problem in which our goal is to design a tour trip with the most desirable sites, subject to various budget and time constraints. We first establish a framework for this problem, and then formulate it as a mixed integer linear programming problem. However, except when the size of the problem is small, say, with less than 20–30 sites, it is computationally infeasible to solve the mixed-integer linear programming problem. Therefore, we propose a heuristic method based on local search ideas. The method is efficient and provides good approximation solutions. Numerical results are provided to validate the method. We also apply our method to the team orienteering problem, a special case of the tour planning problem which has been considered in the literature, and compare our method with other existing methods. Our numerical results show that our method produces very good approximation solutions with relatively small computational efforts comparing with other existing methods.

Keywords

Tour planning problem Team orienteering problem Mixed integer linear programming Heuristic Local search 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Archetti, C., Hertz, A., & Speranza, M. (2007). Metaheuristics for the team orienteering problem. Journal of Heuristics, 13, 49–76. CrossRefGoogle Scholar
  2. Buhalis, D. (2003). eTourism: information technology for strategic tourism management. London: Prentice Hall. Google Scholar
  3. Buhalis, D., & Law, R. (2008). Twenty years on and 10 years after the internet: the state of eTourism research. Tourism Management, 29(4), 609–623. CrossRefGoogle Scholar
  4. Chao, I., Golden, B., & Wasil, E. (1996). The team orienteering problem. European Journal of Operational Research, 88, 464–474. CrossRefGoogle Scholar
  5. Fesenmainer, D. R., Ricci, F., Schaumlechner, E., Wober, K., & Zanella, C. (2003). DIETORECS: travel advisory for multiple decision styles. In Information and communication technologies in tourism (pp. 232–241). New York: Springer. Google Scholar
  6. Hannes, W. (2003). Intelligent system in travel and tourism. In Proceedings of international joint conference on artificial intelligence 2003. Google Scholar
  7. Ke, L., Archetti, C., & Feng, Z. (2008). Ants can solve the team orienteering problem. Computers & Industrial Engineering, 54, 648–665. CrossRefGoogle Scholar
  8. Lin, S. (1965). Computer solutions of the traveling salesman problem. Bell System Technical Journal, 44, 2245–2269. Google Scholar
  9. Or, I. (1976). Traveling salesman-type combinatorial problems and their relation to the logistics of blood banking. Ph.D. thesis, Department of industrial engineering and management science, Northwest University, Evanston, IL. Google Scholar
  10. Potvin, J. Y., Kervahut, T., & Rousseau, J. M. (1996). The vehicle routing problem with time windows part I: tabu search. INFORMS Journal on Computing, 8(2), 158–164. CrossRefGoogle Scholar
  11. Potvin, J. Y., & Rousseau, J. M. (1995). An exchange heuristic for routing problems with time windows. Journal of Operational Research Society, 46, 1433–1446. Google Scholar
  12. Ricci, F. (2002). Travel recommender systems. IEEE Intelligent Systems, 17(6), 55–57. Google Scholar
  13. Ricci, F., & Wether, H. (2002). Case base querying for travel planning recommendation. Information Technology & Tourism, 4(3–4), 215–226. Google Scholar
  14. Schafer, J. B., Konstan, J., & Riedi, J. (1999). Recommender Systems in e-commerce. In Proceedings of the 1st acm conference on Electronic commerce 1999. Google Scholar
  15. Souffriau, W., Vansteenwegen, P., Vanden Berghe, G., & Van Oudheusden, D. (2008). A greedy randomized adaptive search procedure for the team orienteering problem. In Proceedings of EU/Meeting 2008, France, 23–24 October 2008. Google Scholar
  16. Vansteenwegen, P., Souffriau, W., Vanden Berghe, G., & Van Oudheusden, D. (2009). A guided local search metaheuristic for the team orienteering problem. European Journal of Operational Research, 196(1), 118–127. CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Chenbo Zhu
    • 1
  • J. Q. Hu
    • 1
  • Fengchun Wang
    • 2
  • Yifan Xu
    • 1
  • Rongzeng Cao
    • 2
  1. 1.Department of Management Science, School of ManagementFudan UniversityShanghaiChina
  2. 2.IBM China Research LaboratoryBeijingChina

Personalised recommendations