As a comprehensive course, the study travel course is well suited to be offered in higher education. In the context of the country’s great attention to higher education and study travel, the development of study travel courses in higher education is lagging behind. In this paper, we attribute the study tour path planning objective to the TOTSP problem, define the travel time function of TOP path, and solve the TOTSP problem by mixing particle swarm algorithm and genetic algorithm. Using association rules to set up courses in the process of research and study travel, the efficiency of professional course setting of research and study travel is measured by DEA model. The shortest time using the particle swarm algorithm based on time factor is [3.536,4.154]h, and the maximum time saving degree reaches 25.527%. Among the study population, there are 20 courses such as Principles of Management and Corporate Strategy that have been set up to be purely technically effective, accounting for 71.43% of the courses. The remaining 8 courses had a PTE of less than 1. There is still room for improvement in terms of classroom setting efficiency.
