This Engineering Research Initiation (ERI) project support research that aims to enable rapid engineering design optimization involving complex design requirements. Engineering design is an approach for optimizing objective(s) (e.g., minimizing the drag of an airplane) while fulfilling design requirements (e.g., maintaining a lower limit of the lift generated by the airplane). Engineering design has achieved success in broad areas, including automobiles, aircraft, spacecraft, energy systems, and manufacturing equipment. Conventional design optimization, however, faces the following two challenges in practical applications. 1) Objective values and design requirements typically need to be computed hundreds or even thousands of times, which significantly slows down the optimization process. 2) Practical optimization typically involves complex design requirements, which make it difficult to find real optimal solutions. To overcome these challenges, this project will investigate developing an approach that ensures all design requirements are automatically fulfilled during the optimization process. If successful, this approach can reduce optimization complexity and increase optimization efficiency. This project seeks to develop a generative artificial intelligence approach for design requirement fulfillment, along with surrogate models to enable near real-time computation – ultimately supporting rapid engineering design. Generative artificial intelligence can learn from existing