Hybrid Axial Field Flux-Switching Permanent Magnet (HAFFSPM) machine exhibits high power density and torque density. The genetic algorithm within the optiSLang software is utilized for multi-objective optimization of the motor, enhancing magnetic flux amplitude and reducing the peak-to-peak value of cogging torque by modifying stator and rotor parameters. Initially, baseline parameters is established, followed by the modification of several parameters to analyze their impact on performance and determine appropriate value ranges. Subsequently, the optiSLang software is used to generate optimized solutions and the Pareto frontier. The optimal scheme was then selected for comparison with the initial performance metrics. The optimization results indicated a slight increase in magnetic flux amplitude and a significant reduction in the peak-to-peak value of cogging torque, con-firming the feasibility of the optimization approach.