Research On Tourist Route Planning Based On Improved Ant Colony Algorithm

Path planning is a process of seeking an optimal path under certain preconditions.Path planning is becoming more and more relevant to us both at work and in life.There are many application scenarios of path planning,including all kinds of robot path planning,uav flight path planning and all kinds of vehicle route planning.There are many paths planning scenarios closely related to everyone,one of which is optimal route planning for tourists,that is,path planning can plan a suitable travel route for people.There are many ways to realize path planning,including traditional path planning algorithm,graphics method and intelligent simulation algorithm.Ant colony algorithm is one of the most common intelligent simulation algorithms.In the past,some researchers have used ant colony algorithm to carry out path planning,and some achievements have been achieved.In this paper,the basic ant colony algorithm is used to solve the shortest collision free path,and the basic ant colony algorithm is improved,and then the improved ant colony algorithm is used to better plan the shortest collision free path.At the same time,the path planning method is applied to the actual scene,and the improved ant colony algorithm is used to find a suitable travel route for tourists.The main contents of this paper are as follows:1.Establish the path planning map and model,and use the basic ant colony algorithm to solve the shortest collision free path.The shortest collision-free path and the relationship between the number of iterations and the length of the path in the process of finding the shortest collision-free path are obtained.The shortcomings of the basic ant colony algorithm include long search time,easy to fall into local optimization,unable to solve the problem of continuous domain,and strong randomness.In view of the above shortcomings,the improvement scheme of the basic ant colony algorithm is proposed,including changing the transition probability and combining with genetic algorithm.The improved ant colony algorithm is used to plan the shortest collision-free path again.The new shortest collision-free path and the relationship between the number of iterations and the length of the path in the process of finding the shortest collision-free path are obtained.By comparing the two experimental results,it can be seen that the improved ant colony algorithm has faster convergence and higher efficiency in the process of shortest collision free path planning.2.This paper presents a practical problem of path planning and applies the improved algorithm to solve it.Based on the map of Guangxi as the actual background,an optimal route planning model for tourists is established according to several factors that may affect the route of tourists during their journey,including the distance between cities,the degree of urban congestion and the level of desire for each city.The improved ant colony algorithm proposed above is applied to realize the optimal path planning for tourists,and the best tourist route for tourists to travel throughout Guangxi is obtained.The significance of this study lies in the fact that the model established has practical reference value and can solve the new optimal tourist route with the change of preset conditions in the model.