Tuned mass dampers (TMDs) are among the most representative passive vibration control devices and are widely used to suppress vibrations in machinery and high-rise buildings. A notable variant of TMDs is the rolling-pendulum TMD, which consists of a rolling body that moves along an arc-shaped guide attached to the primary structure. Rolling-pendulum TMDs offer excellent durability; however, the auxiliary system still requires a damping mechanism that allows for the easy adjustment of damping force. Although the performance of rolling-pendulum TMDs with magnetic damping has been investigated, this method provides relatively low damping forces compared with other approaches. As an alternative, rolling particle dampers (RPDs) have been proposed, in which a hollow space is created inside the rolling body and partially filled with granular materials. These dampers utilize friction and collisions among the particles to generate damping, making them both cost-effective and easily tunable. However, because of the large number of design parameters involved, the performance of RPDs has not been sufficiently investigated. The aim of this study is to identify optimal parameter combinations to enhance the performance of RPDs through both experimental and numerical approaches. The granular spherical materials used in this study are made of high-carbon chromium steel and are of uniform size. The motion of the primary system is measured with an accelerometer. The motion of the RPDs is analyzed using the discrete element method, and particle swarm optimization is employed to determine the optimal parameter set. The validity of the computational model is then examined by comparing the numerical results with experimental data. Furthermore, the reduction in the maximum amplitude of the primary structure achieved by the optimized RPD configuration is quantified.