In order to solve the problem of load balancing in Software Defined Network (SDN) control plane, a Dynamic Switch Migration Algorithm based on Multi-objective optimization (M-DSMA) was proposed. Firstly, the mapping relationship between the switch and the controller was transformed into 0-1 matrix optimization problem. Then, the two conflicting objective functions were simultaneously optimized and controlled by the multi-objective genetic algorithm based on Non-dominated Sorting Genetic Algorithm-Ⅱ (NSGA-Ⅱ), one was the plane load balancing degree and another one was the communication overhead generated by switch migration. In the process of multi-objective optimization, the individuals were selected by using the fitness function for crossover and mutation, and then a rapid non-dominated sorting method was used to elite strategy in population. The next generation population was generated and the whole population was continually evolved, thus the global optimal solution was searched. The simulation results show that, the proposed M-DSMA can effectively balance the control plane load, and reduce the communication overhead by 30% to 50% compared with Dynamic Switch Migration Algorithm (DSMA). The proposed algorithm has the significant advantages in improving the control plane scalability.