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Optimal individualized multimedia tourism route planning based on ant colony algorithms and large data hidden mining

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Abstract

This paper collects the coordinates of longitude and latitude of each city and the actual inter-city train tickets and air tickets aiming at the route optimization of 34 cities in China. Ant colony algorithm is used for heuristic search on the basis of this large amount of data, and a reasonable and optimal travel route is given for practical problems. At the same time, the increment of pheromone was adjusted by positive and negative feedback, and the volatile factors of pheromone were randomized, it enables the ant colony algorithm to automatically adjust the pheromone amount on the path to improve the performance of the ant colony algorithm. Finally, the performance advantages of the proposed algorithm in personalized tourism route planning are verified by simulation experiments.

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Authors and Affiliations

  1. Department of Tourism and Culture, Anhui Finance and Trade Vocational College, Hefei, China

    Xiaohui Qian & Xiaopeng Zhong

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  1. Xiaohui Qian
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  2. Xiaopeng Zhong
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Correspondence to Xiaohui Qian.

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Qian, X., Zhong, X. Optimal individualized multimedia tourism route planning based on ant colony algorithms and large data hidden mining. Multimed Tools Appl 78, 22099–22108 (2019). https://doi.org/10.1007/s11042-019-7537-0

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  • DOI: https://doi.org/10.1007/s11042-019-7537-0

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