Two-phase induction motors make an important contribution to social welfare. Accordingly, enhanced quality in such motors would benefit society. This study was done to test this type of motor to determine a nonlinear optimal point in the form of a multiobjective function between ripple of the torque and motor efficiency with consideration of a weighted coefficient in an unbalanced-unsymmetrical two-phase induction motor. Tests demonstrated that minimizing total harmonic distortion could reduce torque ripple. The optimal point was determined using optimization algorithms, and a hybrid of genetic and particle swarm optimization algorithms simultaneously in order to increase efficiency and to reduce torque ripple. Findings established the optimized dimensions of the motor. The performance of these optimized dimensions was tested by the finite-element method and the results are shown. Then an experimental model of the motor was produced. Comparison was made for responses obtained from the simulation and experimental model by Park's equations in transient and steady states.