Aiming at the flow shop scheduling problem with limited buffer, a hybrid shuffled frog-leaping algorithm (HSFLA) combining variable neighborhood search (VNS) and frog-leaping algorithm (SFLA) is proposed to minimize the makespan. To improve the quality of the initial solutions, a partial initial population is generated using the NEH algorithm and iterative greedy (IG). In order to avoid the problem of the original algorithm's premature convergence and producing infeasible solutions, the adaptive moving operator is introduced to improve the step size and crossover operator in the sub-population's updating part. A variable neighborhood search method based on three neighborhood structures is designed to enhance the local optimization ability of the algorithm. The performances of HSFLA were evaluated over car and rec benchmark problems. The computational results demonstrated that HSFLA has an effective performance for the flow shop scheduling problem with limited buffer.