Flexible manufacturing systems have become relatively mature in the industrial field, representing the most advanced research achievements in the development of the manufacturing industry. But currently, there are few resources and high costs in universities to create a system that is more practical, and it cannot meet the practical teaching requirements of students in multiple majors. In response to the above issues, this study first designed a flexible manufacturing system from the overall architecture, then introduced and integrated virtual simulation technology, and utilized multi-objective genetic algorithm for cargo location optimization to improve the work efficiency of the flexible system. The research results indicate that after 213 iterations of the proposed algorithm, the iteration curve of the total objective function value tends to be stable, and the effect of cargo location optimization is relatively ideal. At this time, the total objective function value is 142.5. In addition, as the scale expands, the corresponding number of iterations for multi-objective genetic algorithm at its maximum scale is 411.2. The application effect of virtual flexible manufacturing system in practical teaching in universities is good, and visual learning methods can better attract students' attention.