For the joint scheduling of machines and automated guided vehicles(AGVs) in the green hybrid flow shop problem with missing operations, an improved memetic algorithm(MA) is proposed to minimize both the maximum completion time and the total energy consumption, simultaneously. Firstly, a three-layer encoding method based on operations, machines and speeds is designed to ensure the search of the algorithm in the whole solution space to the greatest extent. Then, a hybrid population initialization method is designed to improve the quality of initial population. Meanwhile, crossovers, mutation operators and two kinds of neighbourhood search strategies based on the problem are designed to balance the global and local search ability of the algorithm. Finally, simulation experiments show the superiority of the proposed algorithm in solving the joint scheduling of machines and AGVs in the green hybrid flow shop problem with missing operations.