Abstract 2219 aluminum alloy rings are important part of liquid cryogenic rocket fuel tanks. Residual stress is inevitably introduced in the forming process of the rings due to the nonlinear thermomechanical coupling conditions, which will affect its mechanical properties, fatigue properties, corrosion resistance, and dimensional stability. Thermal vibratory stress relief (TVSR) has great potential in reducing residual stress, and process optimization of TVSR is necessary to further improve its application, but it is rarely reported. In this study, process optimization of roll formed 2219 aluminum alloy rings is conducted. The influence of vibration amplitude, vibration time, vibration frequency, heating time, holding time, and cooling time on TVSR treatment are investigated. Results show that the maximum equivalent residual stress of 2219 aluminum alloy rings can be reduced by 93.6% after optimized TVSR treatment. With the increase in vibration time, heating time, holding time, and cooling time, the maximum equivalent stress decreases. However, the increase in the vibration amplitude results in an increase in the maximum equivalent stress. Further, a genetically optimized artificial neural network intelligent optimization algorithm is applied to quickly predict the TVSR effect of 2219 aluminum alloy rings.