Travel route planning of core scenic spots based on best-worst method and genetic algorithm: a case study

Abstract

Travel has become the most popular way to relieve stress at present. Choosing suitable travel cities and scenic spots among the many alternatives and planning travel routes are the two most troublesome problems for people. For the first question, this paper uses the multi-criteria decision-making method—best-worst method (BWM) to build a priority model of core scenic spots to help people filter out the cities and core scenic spots with the highest travel value from a large number of tourist attractions. For the second question, this paper uses the genetic algorithm to plan the travel route of core scenic spots, so as to reduce the cost of tourists in the travel process and improve the travel happiness as much as possible. Subsequently, a case about the selection of core scenic spots and travel route planning in Hubei Province of China was presented. Among them, 6 cities (i.e. 24 core scenic spots) with the highest travel priority were selected by the score of BWM. Then, the genetic algorithm was programmed by MATLAB to obtain the optimal travel routes of these 24 core scenic spots, with a total distance of 1355.72 km. This paper will promote the practical application of BWM and genetic algorithm.