Optimization involves finding the "best" solution according to specified criteria. In Engineering Design, this might typically be minimum cost or weight, maximum quality or efficiency, or some other performance index pertaining to a disciplinary objective. Realistic optimal design involves not only an objective function to be minimized or maximized, but also constraints that represent limitations on the mathematical design space. Numerical program ming requires the mathematical representation of the design space in terms of "design variables", which are parameters that signify some potential for change. Generally, the problems of interest in engineering are of a nonlinear nature; the dependence of the objective function and constraints on the design variables is not linear. Engineering Optimization I (MAE 550) introduces the traditional nonlinear optimization methods that can be used to solve a wide variety of design problems across all engineeri ng disciplines. This course will address newer topics not covered in MAE 550; many such techniques are less based on gradient-based calculus, and based more on rigorous experience and successful usage. "Heuristics", if you will.