Grey wolf optimization(GWO) algorithm is applied to the flexible job shop scheduling problem(FJSP), and a hybrid GWO(HGWO) is proposed with the objective of minimizing the makespan. Firstly, a two-phase encoding method is employed, and a mapping relationship is set up between the continuous space and the discrete space of FJSP.Then, a population initialization strategy is designed to ensure the quality of the initial solutions, and then a variable neighborhood search(VNS) strategy is embedded to enhance the local search ability. In addition, genetic operators are introduced to improve the global exploration capability of the algorithm. Finally, experimental data show that the proposed HGWO is effective for solving the FJSP.