The short course is intended to provide an introduction to constrained optimization models. After providing an overview of the major steps in formulating a model, the major types of modeling approaches, and how these methods compare to traditional health economic modeling and simulation methods, the course will cover linear programming in some detail. Linear programming is the most straightforward of the constrained optimization methods but also fundamental to understanding other techniques that can account for complexities such as nonlinearities, uncertainty, decisions which unfold dynamically over time, and multiple competing objectives. In addition to discussing a graphical approach to linear programming models the simplex method will be presented. The simplex method is the most widely used algorithm for solving linear programs with large numbers of constraints and inputs. Finally, the course will include a hands-on exercise where students formulate the mathematical representation of a linear program to maximize public health subject to budget constraints.