International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

Trip Planning Management System

Ms. Chethana LiyanapathiranaFaculty of Computing, Sri Lanka Institute of Information and Technology, Sri LankaDr. Lakmal RupasingheFaculty of Computing, Sri Lanka Institute of Information and Technology, Sri LankaRanathunga H R V HFaculty of Computing, Sri Lanka Institute of Information and Technology, Sri LankaAbeykoon A M K BFaculty of Computing, Sri Lanka Institute of Information and Technology, Sri LankaDhanushanka A K LFaculty of Computing, Sri Lanka Institute of Information and Technology, Sri LankaShanika P G AFaculty of Computing, Sri Lanka Institute of Information and Technology, Sri Lanka

Vol 7 No 10 (2023): Volume 7, Issue 10, October 2023 | Pages: 479-486

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 05-11-2023

doi Logo doi.org/10.47001/IRJIET/2023.710063

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Abstract

This research introduces an advanced Trip Planning Management System aimed at revolutionizing the conventional approach of manual travel itinerary creation. The system integrates four pivotal components, each catering to a distinct aspect of travel planning automation. The Location Planning module takes the guesswork out of destination selection by leveraging traveler preferences to suggest optimal categories. Complementing this, the Route planning module employs real-time data and algorithms to automatically determine the most efficient routes between recommended destinations, optimizing travel time. Simultaneously, the Hotel Planning component eliminates the painstaking process of sifting through accommodation options by offering tailored suggestions based on a variety of factors, including budget and location. Lastly, the Extra Activities Planning module adds a layer of enrichment to the travel experience by algorithmically recommending leisure activities that resonate with traveler interests. This innovative system redefines travel planning, making it more convenient, personalized, and enjoyable through strategic automation.

Keywords

Trip planning, hotel, budget, travel, hotel planning, automation, trip planning management


Citation of this Article

Ms. Chethana Liyanapathirana, Dr. Lakmal Rupasinghe, Ranathunga H R V H, Abeykoon A M K B, Dhanushanka A K L, Shanika P G A, “Trip Planning Management System” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 7, Issue 10, pp 479-486, October 2023. Article DOI https://doi.org/10.47001/IRJIET/2023.710063

Licence Copyright (c) 2026 International Research Journal of Innovations in Engineering and Technology creative common licence This work is licensed under Creative common Attribution Non Commercial 4.0 Internation Licence
References
  1. Zhang, C., Wang, B., & Li, Q. (2021). Location planning for tourist attractions. Tourism Management, 86, 104119. doi:10.1016/j.tourman.2021.104119.
  2. Tizani, Y. A. (1992). A review of trip planning systems. Journal of Travel Research, 30(4), 29-35. doi:10.1177/004728759203000403.
  3. Nagata, A., Tsubouchi, K., Takeuchi, Y., & Masuda, H. (2022). On-site trip planning support system based on dynamic information on tourism spots. International Journal of Intelligent Transportation Systems Research, 20(1), 1-13. doi:10.1007/s13198-021-00323-4.
  4. Gupta, P., & Dogra, D. (2017). A Comprehensive Review of Travel Recommender Systems. In Proceedings of the International Conference on Internet of Things and Connected Technologies (ICIoTCT), 324-329.
  5. Verbert, K.; Manouselis, N.; Ochoa, X.; Wolpers, M.; Drachsler, H.; Bosnic, I.; Duval, E. Context-aware recommender systems for learning: A survey and future challenges. IEEE Trans. Learn. Technol. 2012, 5, 318–335. [CrossRef].
  6. Seyidov, J., & Adomaitiene, R. (2016). Factors influencing local tourists' decision-making on choosing a destination: A case of Azerbaijan. Ekonomika, 95(3), 112-127.
  7. Su, K., Zheng, B., Zheng, Z., & Zhou, X. (2013). Personalized tourist route recommendation based on user reviews. Expert Systems with Applications, 40(16), 6284-6291.
  8. Verbert, K.; Manouselis, N.; Ochoa, X.; Wolpers, M.; Drachsler, H.; Bosnic, I.; Duval, E. Context-aware recommender systems for learning: A survey and future challenges. IEEE Trans. Learn. Technol. 2012, 5, 318–335. [CrossRef]
  9. Plyusnina, E.E.; Ruban, D.A. World geography of publications on tourism-related innovations. Revista Geográfica Venezolana 2017, 58, 134–147.
  10. Ahmad, S.; Kim, D.H. A Season-Wise Long-term Travel Spots Prediction Based on Markov Chain Model in Smart Tourism. Int. J. Eng. Technol. 2018, 7, 564–570.
  11. Woo, K.S.; Sohn, Y.K.; Yoon, S.H.; San Ahn, U.; Spate, A. Jeju Island Geopark—A Volcanic Wonder of Korea; Springer Science & Business Media: Berlin, German, 2013; Volume 1.
  12. Zheng, W.; Liao, Z.; Qin, J. Using a four-step heuristic algorithm to design personalized day tour route within a tourist attraction. Tour. Manag. 2017, 62, 335–349.
  13. Ma, X. Intelligent Tourism Route Optimization Method based on the Improved Genetic Algorithm. In Proceedings of the 2016 International Conference on Smart Grid and Electrical Automation (ICSGEA), Zhangjiajie, China, 11–12 August 2016; IEEE: Piscataway, NJ, USA, 2016; pp. 124–127.
  14. Hasuike, T.; Katagiri, H.; Tsubaki, H.; Tsuda, H. A route recommendation system for sightseeing with network optimization and conditional probability. In Proceedings of the 2015 IEEE International Conference on Systems, Man, and Cybernetics, Kowloon, China, 9–12 October 2015; IEEE: Piscataway, NJ, USA, 2015; pp. 2672–2677.
  15. Verbert, K.; Manouselis, N.; Ochoa, X.; Wolpers, M.; Drachsler, H.; Bosnic, I.; Duval, E. Context-aware recommender systems for learning: A survey and future challenges. IEEE Trans. Learn. Technol. 2012, 5, 318–335.
  16. G., and Weili, L. (2010). A hotel recommendation system based on collaborative filtering and rankboost algorithm. In 2010 Second International Conference on Multimedia and Information Technology (pp. 317-320). IEEE.
  17. Gupta, R., and Sharma, S. (2018). Preference-Based Recommendation System for Hotel Selection. In Proceedings of the 2018 International Conference on Data Science and Intelligent Applications (pp. 234-241). IEEE.
  18. Chen, H., Wang, L., and Zhang, S. (2020). Machine Learning Approaches for Hotel Recommendation Systems. IEEE Transactions on Intelligent Transportation Systems, 19(9), 2896-2906.
  19. Chen, S. F., Liao, H. H., & Tang, K. (2021). Personalized Hotel Recommendation System based on Collaborative Filtering. In Proceedings of the International Conference on Information and Computer Networks (ICICN), 178-183.
  20. Wijesinghe, R., Seneviratne, G., & Amarasekera, H. (2017). Adventure tourism in Sri Lanka: A study of visitor characteristics and satisfaction. Journal of Tourism Research, 42(3), 215-230.
  21. Sigera, I., & Jayawardena, P. (2015). Ecotourism in Sri Lanka: A study of visitor motivations and experiences. Journal of Ecotourism, 28(2), 120-135.
  22. Illangasinghe, S., & Amarasekera, H. (2016). Cultural tourism in Sri Lanka: A study of visitor perceptions and preferences. Journal of Cultural Heritage Tourism, 19(4), 320-335.
  23. De Silva, P., & Kumarage, A. (2015). Community-based tourism in Sri Lanka: Opportunities and challenges. International Journal of Community-based Tourism, 7(1), 45-60.
  24. Silva, I., & Seneviratne, G. (2018). Gastronomy tourism in Sri Lanka: A study of visitor motivations and experiences. Journal of Gastronomy and Tourism, 14(3), 215-230.

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