A novel multi-objective optimization design method for permanent magnet roller based on improved particle swarm optimization algorithm and RMxprt co-simulation was developed to address the issue of low optimization efficiency when relying solely on expert experience. Firstly, an improved particle swarm optimization algorithm was proposed to enhance the convergence speed of the optimization process. Secondly, based on the analysis of the relationship between the structural and performance parameters of the permanent magnet roller, the variable parameters, constraint parameters, and optimization parameters for the improved particle swarm optimization algorithm were determined. Lastly, a MATLAB program for the improved particle swarm optimization algorithm was developed to achieve closed-loop iteration and comparative optimization of the input and output parameters in RMxprt, thereby improving the efficiency and effectiveness of the optimization design for the permanent magnet roller.