Rayleigh wave exploration predominantly exploits the dispersion characteristics inherent in Rayleigh waves to elucidate the properties and structural modifications of subsurface media.In recent years, this methodology has been extensively employed to address critical issues, including geological structure identification, medium characterization analysis, earthquake risk assessment, and mineral resource exploration.Nonetheless, the inversion of Rayleigh wave dispersion curves encounters significant challenges, including slow convergence rates, noise interference, and the propensity to converge to local minima.This paper introduces a Tikhonov regularization and optimization algorithm specifically designed for the inversion of Rayleigh wave dispersion curves.This methodology incorporates the L1 norm of the model to impose sparse regularization constraints throughout the inversion modeling process.This approach enhances the model's generalization capacity, mitigates errors arising from layer refinement, improves inversion accuracy, and aligns the inversion results more closely with the real geological model.In the context of sparse regularization models, the Alternative Direction Method of Multipliers (ADMM) is utilized to address the minimization problem and ascertain the optimal solution.Empirical testing conducted with theoretical geological models and real data demonstrates that the method proposed in this study exhibits enhanced inversion accuracy and superior stability compared to the traditional least squares method.