Travel Route Planning Based on Genetic Algorithm and Greedy Algorithm

Abstract

Based on genetic algorithm and greedy algorithm, this study proposes a scientific tourism route planning model to maximize tourists' visiting experience and cost-effectiveness. Firstly, this paper pre-processed the data of 352 Chinese cities and their 35,200 attractions, and screened out the 50 most attractive cities by using principal component analysis and TOPSIS method, taking into account factors such as city size. Subsequently, tourists' travel route planning was optimized based on genetic algorithm. Finally, greedy algorithm was introduced to study the customized routes under different tourism needs, such as mountain view tourism routes, to optimize the multiple indicators involved. This study not only provides foreign tourists with personalized travel plans, but also successfully achieves a balance between economy and efficiency under the premise of guaranteeing tourists' reasonable time and cost.