Analysis of Tourism Development Based on Multiobjective Optimization and Simulated Annealing Algorithm

The purpose of this study is to use computer algorithms to construct an analytical model of tourism development, which can help the city to realize the sustainable development of tourism and provide a reference for other regions. The study builds a sustainable tourism index model with the help of multi-objective optimization and simulated annealing algorithm. In the data processing stage, multi-source data are collected and used for model training after data cleaning, feature engineering and other pre-processing. In the modeling process, multiple influencing factors are classified and quantified, and the weights of each index are optimized by simulated annealing algorithm, and the Pareto optimization algorithm is used to obtain the global optimal solution. The advantage of this model is that the parameters can be adjusted according to different regional characteristics. Meanwhile, the research results provide scientific quantitative decision support for tourism management and promote the digital and intelligent development of tourism industry.