Estimating the shear wave velocity and thickness of geologic units in a sedimentary structure is important for quantifying the local site effect caused by an earthquake. Inversion of the Rayleigh wave dispersion alone is sensitive to the absolute average shear wave velocity, while the H/V spectral ratio is sensitive to velocity contrasts. The solution of these models in a joint system using conventional inversion techniques suffers from difficulties while evaluating partial derivatives, dependencies to the initial model that is sometimes difficult to estimate, and trapping at a local minimum. Herein, a joint model using the Pareto optimality technique with multiobjective particle swarm optimization was constructed as an effective global optimization method to decrease weakness and increase performance while estimating the depths and velocities. The presented approach is a multiobjective optimization method that does not require weighting, and allows evaluations of the individual objective function separately in a joint system. This study presents 2 synthetic joint system examples to account for a gradient-type and sharp velocity contrast cases, and an application from field data obtained from the Bursa Basin in Turkey. With these examples, an automated parameter search space was demonstrated to account for the abrupt velocity changes and a number of additional key points that are essential for a reasonable optimal solution.