Aiming at the distributed permutation flow shop scheduling problem with variable processing speed, a double population algorithm is proposed to optimize the maximum completion time and the total energy consumption of the machine. Firstly, an initialization method that mixes four strategies is used to generate a high-quality initial population. Secondly, specific evolution methods are designed according to the characteristics of the two pop-ulations, and the dynamic guide factor is introduced to adjust the evolution mode of the population. At the same time, an energy-saving strategy for speed regulation is proposed to further optimize energy consumption. Finally, a dynamic population strategy is proposed to balance the resources of the two populations. The effectiveness of each strategy is proved by simulation experiments, and compared with other algorithms, the results show that the proposed algorithm has obvious advantages.