Application of an algorithm for scenic route recommendations during selective sightseeing

Existing popular scenic route recommendations essentially choose a tourist route according to the popularity of the attractions and the available time of the tourists. The recommended routes rarely take either the individual needs of tourists or the efficiency of the tour into account. This paper presents a selective tour for route recommendation (STRR) algorithm for selective tours based on individualization and tour efficiency. This algorithm makes the spatial structure of the scenic area discrete and generates the optimum tourist attractions. Based on the discrete particle swarm optimization (PSO) method, this algorithm proposes a method to improve location update by using the priority rules. It can quickly generate the shortest route which meets the individual needs of tourists. This paper takes the East Campus of Beijing University of Chemical Technology as an example to carry out plane simulations. The experimental results show that the STRR algorithm can generate a route that satisfies the individual needs of tourists whilst also being the most efficient. The new algorithm has been shown to be more efficient in terms of calculation than other algorithms.