Abstract: Aiming at the issue of flexible workshop production scheduling, a multi-objective sparrow search algorithm (MOSSA) was designed to solve the problem with the objective function of minimizing the completion time, the sum of machine load and the whole machining cost. First, the population after the fusion of father and son was sorted by non dominated order, and the best position individual and the worst position individual were selected, respectively. Second, the two-stage rule was used to code the machine selection and process sequencing. Finally, the sparrow search algorithm was used to update and optimize the population.Experimental simulations were carried out through calculation examples to study the influence of parameters on MOSSA, and compared MOSSA with other algorithms. Results show that under this model, the influence of parameters is little, and MOSSA has high-performance global search capabilities and good convergence. It has a guiding role to solve the problem of multi-objective production scheduling.