The search of bearing geometry and performance which satisfies at best design objective along with design criteria is not so easy task. Design optimization of hydrodynamic bearings is very complex in nature. The complexity and time consuming nature of the design process of hydrodynamic bearings warranted the development of a new methodology. The purpose of this study is to use of the genetic algorithm in the optimal design of a three-lobe preloaded fluid film bearing in essence developing the bearing configurations that optimize power loss along with other design criteria namely fluid film thickness, stability parameter, film temperature, and film pressure. The results obtained and presented in this study are compared to results from numerical optimization methods such as gradient-based method, and show the potential of the genetic algorithm in optimization of three-lobe preloaded hydrodynamic bearings. This robust method has been designed to search for most feasible solutions to problems and has gained recognition in many fields.