Hybrid flow shop scheduling problems have been extensively addressed in single factory, however, distributed hybrid flow shop scheduling problems(DHFSP) are seldom investigated in multiple factories. In this study, the DHFSP with sequence-dependent setup times is studied and a multi-class teaching-learning-based optimization (MTLBO) algorithm is proposed to minimize makespan and maximum tardiness simultaneously. A two-string representation is adopted. The s classes are formed and the evolution of each class consists of two teacher phases and one learner phase. Class evaluation is introduced, a reward and punishment mechanism is executed on classes, and elimination process is also applied. A number of experiments are conducted and the computational results demonstrate that the MTLBO is very competitive for the DHFSP.