For flexible shop scheduling in the case of machine resources and processing route selectable, a flexible shop model is established with minimum and maximum completion time and time penalty costs as targets. According to the characteristics of the problem, an improved firefly algorithm is proposed. The algorithm designs a coding strategy with greedy ideas. A firefly individual represents the processing sequence and process processing position. It adopts an adaptive selection strategy to adapt the step length and improve the accuracy of the algorithm. The introduction of POX cross strategy to improve the algorithm's local and global optimization capabilities, and the use of greed to improve the convergence speed of the algorithm. The performance of the algorithm is verified by comparison with example simulations and algorithms. The experimental results show that the improved firefly algorithm is effective for solving the flexible shop scheduling problem.