Research Of Intelligent Tourism Route Planning Based On Ant Colony Algorithm

Tourism route planning is very significant in tourism.Compared with the subjective route planning,it is more scientific and persuasive to establish a mathematical model to solve the tourism route planning.In this paper,we mainly study the traveling salesman problem based on the improved ant colony algorithm,the self driving route planning problem and the intelligent traveling route planning problem.First of all,this paper presents an improved ant colony algorithm for traveling salesman problem.In order to apply the ant colony algorithm to solve the traveling route planning problem,we need the ant colony algorithm can obtain the optimal solution with large probability.In this chapter,the path selection probability and pheromone update rule of the basic ant colony algorithm are improved.The local search of the optimal path is carried out,and the solution process is optimized.Through the performance simulation analysis,the search precision of the algorithm is higher and the solution time is shorter.Secondly,this paper studies the self driving route planning problem.On the basis of traveling salesman problem,the mathematical model is established with the minimum number of travel days.In the process of solving the problem,the regional division of the scenic spots is carried out by the reasonable rules,and an improved ant colony algorithm is used to solve the regional route.Finally,this paper studies the problem of intelligent tourism route planning.On the basis of self driving route planning problem,the mathematical model of this problem is established,which is based on the best travel cost and travel experience.Based on the travel time,this paper puts forward the concept of tourism experience.In the process of solving the problem,the two objectives are transformed into a single objective to solve the problem.