With the development of the manufacturing industry, the profits of enterprises are affected by the timely delivery of products, which is very important for optimizing flexible workshop scheduling. Regarding the flexible workshop scheduling problem, we have proposed three optimization goals. These three goals are respectively, minimizing the completion time of the workpiece, minimizing carbon emissions as small as possible, and minimizing the machine load as the goal of the workshop scheduling problem. In this paper, the dragonfly algorithm is adopted as the optimization algorithm. To further enhance the optimization ability of the algorithm, the sine-cosine algorithm is adopted by us to improve the random walk strategy of the dragonfly. Meanwhile, to further optimize the algorithm, we have adopted inserted greedy decoding. Experimental results show that by using the improved dragonfly algorithm, the optimization effect is significant, which can effectively shorten the processing time of the workpiece. Based on the instance data of a certain manufacturing industry, we designed an experiment. During the experiment, we compared the MODA algorithm with the MOPSO algorithm and the MOGOA algorithm. The experimental results show that the improved dragonfly algorithm has a significant effect in terms of flexible scheduling problems.