Analysis of Tourism Development Based on Multi-objective Optimization and Genetic Algorithm

This study focuses on building an intelligent modeling framework that can promote the long-term development of urban tourism. Firstly, the linear regression model is used to analyze tourism and other related multidimensional data in depth, accurately predict the influence of various factors on urban tourism, and then build a sustainable tourism model based on a multi-objective optimization algorithm. Next, the genetic algorithm is used to simulate the natural selection mechanism in biological evolution, and intelligent optimization of tourist flow and tax parameters is carried out. Finally, in terms of model expansion application, the SGAE model is used to classify the attractions using typical tourist attractions as samples and adjust the weights of model parameters in a targeted manner. Through the innovative method of multi-algorithm fusion, this study effectively copes with the complexity of tourism development and provides an efficient technical support program for the long-term development of the tourism industry.