In Japan, thermal power generation is one of the important power sources after the Great East Japan Earthquake in 2011. On the other hand, some thermal power plants were damaged by the Great East Japan Earthquake or Hokkaido Eastern Iburi Earthquake in 2018, therefore strengthening of seismic performance of thermal power plants has been required for reliable power supply against large earthquakes that will occur in the future. The authors have proposed an application of visco-elastic dampers to a boiler structure in a coal-fired power plant to improve seismic performance. The application of dampers was effective to reduce the base shear force of a support structure of the boiler, and the dampers had a long lifetime for continuous deformation. In our past papers, the parameters were selected manually. However, to design proper parameters and distribution of the dampers on manual is laborious works with many seismic response analyses. Therefore, the genetic algorithm was introduced to the parameter selection of dampers in this paper. The genetic algorithm is one of the optimization algorithms that was inspired by the evolution process of creatures. The genetic algorithm creates a virtual population having genes in the computer, and only individuals with high fitness remain while repeating generational changes. In this paper, parameters of dampers that can reduce the base shear force were searched by the genetic algorithm. This approach can be applied to vibration controls for other industrial facilities.