To solve the flow shop scheduling problem with limited buffers and machine processing gears (FSSP_LBMPG), this research establishes a mathematical programming model for green flow shops with limited buffers. The model has two objective functions: the minimized values of maximum completion time and processing energy consumption. With buffer capacity as a constraint, the processing speed and energy consumption are coordinated by reasonably selecting machine processing gears. Based on the characteristics of the problem model, an improved dandelion optimization algorithm (IDOA) is proposed. The algorithm first designs a DOA double-layer real-valued encoding mechanism to represent the solution to the problem according to the characteristics of the scheduling problem. By introducing an initialization mechanism, the quality and efficiency of the initial solution are improved. During algorithm iteration, a real-valued crossover strategy and a variable neighborhood search strategy are designed to compensate for the poor local search ability of the original dandelion algorithm and enhance the development capabilities of the improved algorithm. Comparative experiments on designed cases show that the proposed improved algorithm effectively enhances the performance of the original algorithm, thereby verifying the effectiveness and robustness of the improved algorithm.