Abstract
Today, tourists pay more attention to the planning of travel itineraries to get a better travel experience. On the premise of knowing the tourist’s point of interest and the traffic information of the tourist route, this paper designs a travel itinerary planning model which can achieve the goal of the shortest total time consuming, the least cost and more humanity. The model draws on the idea of traveling salesman problem (TSP), taking Chengdu as an example, uses the genetic algorithm to carry on the empirical research. In order to obtain better results, some improvements have been made to the coding methods, selection operators, crossover operators, mutation operators and population size in genetic algorithm. Taking the analytic hierarchy process (AHP), we carry out the comparison and similarity evaluation between Chengdu’s popular routes recommended by the tourist websites and the route results obtained by the algorithm to verify the rationality of the model.
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This work is supported by Sichuan Province Philosophy and Social Science Planning Research Project Fund (SC15E035).
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Yan, S., Huang, Y., Wang, X., He, Y., Zhao, L. (2019). Research on the Application of Genetic Algorithm in Urban Travel Itinerary Planning—A Case Study of Chengdu City, China. In: Xu, J., Cooke, F., Gen, M., Ahmed, S. (eds) Proceedings of the Twelfth International Conference on Management Science and Engineering Management. ICMSEM 2018. Lecture Notes on Multidisciplinary Industrial Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-93351-1_35
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DOI: https://doi.org/10.1007/978-3-319-93351-1_35
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