Abstract
Tour route planning is hot research issue of smart tourism and tourism GIS. Reasonable tour route can help tourists get best motive benefit satisfaction. According to common tour route planning method and existing problems, smart tour route planning algorithm based on clustering center motive iteration search is brought forward in the study. Tourist sight data set and subset are set up and interest tourist sight empty vector is formed to store optimal interest tourist sight. Based on individual needs, tourist’s temporary accommodation in the downtown is set as clustering center to build optimal tourist sight extracting algorithm. Motive iteration interval and sub-interval are defined to build one-way shortest path algorithm to output shortest path between clustering center and tourist sight and between two tourist sights. Combining with positive and negative motive benefit impact factors, sub motive iteration values and motive iteration values are formed by iteration functions. Then descending order complete binary tree is generated to output and store motive iteration values and the optimal closed-loop structure with tour route, meanwhile, sub-optimal closed-loop structures with tour routes are also output. Experiment is designed and performed, sample tourists are selected to provide interest needs, and optimal tourist sight generation tree, all closed-loop structures and motive iteration values are obtained. Experiment indicates that the algorithm can solve problems of common tour route planning, meet the individual needs of tourists and provide them with optimal tourist sights and route to get best motive benefits.
Highlights
Tour route planning is hot research issue of tourism GIS in smart tourism
In order to solve the problems, smart tour route planning algorithm based on clustering center motive iteration search is brought forward in the study
Aim at the research background of current tour route planning, traditional tour route planning method and algorithms are brought forward by former researchers, existing problems are analyzed in the research, and smart tour route planning algorithm based on clustering center motive iteration search is brought forward to solve the problems
Summary
Tour route planning is hot research issue of tourism GIS in smart tourism. Before visiting an unfamiliar city, tourists usually make a schedule for the whole trip, in which tour route planning is necessary. As to the aim of increasing tourists’ satisfaction, researchers have done much work on tour route planning algorithm, which mainly focus on using smart algorithm to develop the shortest path by connecting all tourist sights. The main research questions and contents include interest tourist sight extracting algorithm, one-way shortest distance algorithm, optimal tour route planning algorithm and experiment verification. The problems of current tour route planning and bring forward a new thought to set up smart tour route planning algorithm based on clustering center motive iteration search, whose aim is to meet tourists’ individual needs and try to decrease cost while get best motive benefit. This section includes one-way shortest distance algorithm and optimal tour route planning algorithm based on motive benefit influence factors. The study contents and results are concluded, which include research questions solving, academic implications, imitations of the paper and future studies and recommendations
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