Airfield design is challenging for several reasons. It is limited by various constraints, such as airport usability, airspace clearance standards and geometric specifications. In addition, many factors must be considered, such as environmental issues, construction cost, obstructions, winds, runway exits and airport accessibility. The conventional runway design process relies on trial-and-error. It is laborious and usually suboptimal. Thus a mathematical model can help reduce the design time and improve the design quality.

In this thesis, three models are developed for runway design optimization. The first model identifies feasible runway orientations based on crosswind limitations, the second optimizes runway location and orientation, and the third optimizes runway longitudinal-grade design. Various constraints and cost components are considered in the models. Genetic algorithms (GAs) are adopted in order to solve this problem, while a "Feasible Gates" method is used to reduce the search space and enhance computation efficiency.