Tourism Route Management Planning of the Belt and Road Cities Based on Greedy Optimization Algorithm

The study proposes a tourism route management planning design based on greedy optimisation algorithm, combining hotel attraction rating recommendation and tourism route planning algorithms to construct a tourism system. The experimental results show that the average F1 value of the hotel attraction rating recommendation model is 0.91, the average F1 value of the fuzzy neural rating recommendation model is 0.82, and the average F1 value of the review text recommendation model is 0.85. The running time of the dynamic planning-based algorithm is stable at 0.21 s, and the running time of the greedy optimisation-based algorithm is finally stable at 0.19 s. The intelligent management of tourist routes proposed by the research Planning system accuracy, stability, user satisfaction and a comprehensive score are higher than 0.9 points, especially the user experience and satisfaction score is 0.93 points, to meet user needs.