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Trip Itinerary Generation with 2-Opt Algorithm

Published:17 January 2023Publication History

ABSTRACT

Advances in digital technologies and communications are impacting how people travel. However, there are still lacking of personalised digital-based tools to support people in trip planning. Although there are a number of widely used trip planner applications, these applications may not be effective in generating trip itinerary as they do not take into account of user trip preferences and the total travel time to spend. In this paper, we proposed a heuristic search algorithm based on 2-opt to generate trip itinerary. A proof of concept mobile application for trip planning is developed to demonstrate the validity of our method.

References

  1. G. A. Croes. 1958. A method for solving traveling-salesman problems. Oper. Res. 6, 6 (1958), 791–812.Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Paula da Costa, Jason Rhuggenaath, Yingqian Zhang, Alp Akcay, and Uzay Kaymak. 2021. Learning 2-Opt heuristics for routing problems via deep reinforcement learning. SN Comput. Sci. 2(2021), 388.Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Matthias Englert, Heiko Röglin, and Berthold Vöcking. 2017. Smoothed analysis of the 2-Opt algorithm for the general TSP. ACM Trans. Algorithms 13, 1 (2017), 1–15.Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Yu-Ling Hsueh and Hong-Min Huang. 2018. Personalized itinerary recommendation with time constraints using GPS datasets. Knowl. Inf. Syst. 60(2018), 523–544.Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Meng-Tse Lee, Bo-Yu Chen, and Ying-Chih Lai. 2020. A hybrid tabu search and 2-opt path programming for mission route planning of multiple robots under range limitations. Electronics 9(2020), 534.Google ScholarGoogle ScholarCross RefCross Ref
  6. Kwan Hui Lim, Jeffrey Chan, Christopher Leckie, and Shanika Karunasekera. 2018. Personalized trip recommendation for tourists based on user interests, points of interest visit durations and visit recency. Knowl. Inf. Syst. 54(2018), 375–406.Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Mapbox 2021. Mapbox Matrix API. Mapbox. https://docs.mapbox.com/android/java/guides/directions-matrix.Google ScholarGoogle Scholar
  8. Matan Mor and Sagi Dalyot. 2018. Computing touristic walking routes using geotagged photographs from Flickr. In Adjunct Proceedings of the 14th International Conference on Location Based Services (Zurich, Switzerland). ETH Zurich, 63–68. https://doi.org/10.3929/ethz-b-000225591Google ScholarGoogle ScholarCross RefCross Ref
  9. Wen-Bao Qiao and Jean-Charles Créput. 2018. Massive 2-opt and 3-opt moves with high performance GPU local search to large-scale traveling salesman problem. In Learning and Intelligent Optimization(Lecture Notes in Computer Science, Vol. 11353). Springer, Cham, 82–97.Google ScholarGoogle Scholar
  10. Septia Rani, Kartika Nur Kholidah, and Sheila Nurul Huda. 2018. A development of travel itinerary planning application using traveling salesman problem and k-Means clustering approach. In Proceedings of the 7th International Conference on Software and Computer Applications (Kuantan, Malaysia). ACM, 327–331. https://doi.org/10.3929/ethz-b-000225591Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Lahari Sengupta, Radu M-I, and Pasi Fränti. 2018. Planning your route: where to start?Comput. Brain Behav. 1(2018), 252–265.Google ScholarGoogle Scholar
  12. Kendall Taylor, Kwan Hui Lim, and Jeffrey Chan. 2018. Travel itinerary recommendations with must-see points-of-interest. In Companion Proceedings of the The Web Conference 2018 (Lyon, France). International World Wide Web Conferences Steering Committee, Republic and Canton of Geneva, CHE, 1198–1205. https://doi.org/10.1145/3184558.3191558Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Wolfgang Wörndl, Alexander Hefele, and Daniel Herzog. 2017. Recommending a sequence of interesting places for tourist trips. Inf. Technol. Tour. 17, 1 (2017), 31–54.Google ScholarGoogle ScholarCross RefCross Ref

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    • Published in

      cover image ACM Other conferences
      AISS '22: Proceedings of the 4th International Conference on Advanced Information Science and System
      November 2022
      396 pages
      ISBN:9781450397933
      DOI:10.1145/3573834

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 17 January 2023

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      Acceptance Rates

      Overall Acceptance Rate41of95submissions,43%

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