Research On The Optimization Design Of Tourist Routes Based On Intelligent Algorithms

In recent years,with the development of the city and the implementation of the great Tourism and poverty alleviation strategy in Guizhou Province,the tourism industry has become one of the strategies for the transformation and development of Liupanshui,Liupanshui was built in 1978,it is the largest coalfield south of the Yangtze river,karst landform and rocky desertification zone.convenient transportation,it is one of the Southwest important railway hub cities and logistics centers.Have good tourism resources,for the development of tourism has laid a good foundation.With the rapid development of tourism,the traditional fixed single travel routes has not satisfied the needs of consumers.Designing a reasonable and diversified tourist route has become an urgent problem to be solved in the tourism industry.The design of tourist routes is mainly divided into tourism node selection and node combination optimization.Aiming at the selection of tourism nodes,mainly considering the influence factors of tourists,nodes,and roads,and using the importance of random forest metrics and attraction scores,a node screening comprehensive evaluation model was established to obtain a set of nodes that meet a certain demand of tourists.The importance of using random forest measures for influencing factors and scenic spot ratings.A node screening comprehensive evaluation model is established to obtain a set of nodes meeting a certain demand of tourists.Node combination optimization,the method can be divided into traditional and intelligent algorithm,this paper mainly uses ant colony algorithm in intelligent algorithm.Aiming at the existing disadvantages of basic ant colony algorithm,such as:convergence speed is too long,easy to appear local optimization,mainly from pheromone,probability selection formula and the introduction mutation search operation to improve the basic ant colony algorithm,in order to verify the performance of the improved ant colony algorithm,we first extracted 5 test sets in the international standard test library TSPLIB,respectively: bayg29,eil51,eil76,eil101 and ch150,and the results of the experiment are compared with those of the basic ant colonyalgorithm,the literature [6] and [19].the results show that the performance of the improved algorithm has improved significantly.Secondly,in the real problem of Chinese traveling trader(CTSP),3 sets of data are tested,the results show that the improved algorithm is significantly enhanced.On the whole,the improved ant colony algorithm has obvious feasibility,effectiveness and global optimization ability both in solving simulation problem and concrete practical problem.Using the node comprehensive evaluation model proposed in this paper and the improved ant colony algorithm,the tourist routes in Liupanshui City are optimized and designed.According to the different requirements of tourists,a more reasonable and effective diversified tourist route can be obtained.After exchanging with Liupanshui's travel agencies and the CBRC,they all think that the design model of tourism routes in this paper is good,and they can be the basis and reference for their future tourism planning.They have reference and guidance significance for them.