This course introduces students to deterministic optimization models in operations research.  Students learn to formulate, analyze, and solve mathematical optimization models that represent real-world problems.  Only deterministic models are considered, i.e., no uncertainty in the models is allowed.  The first part of the course covers linear programming, the simplex algorithm, and related topics.  The second part of the course discusses other types of optimization models such as various network models.  The third part of the class discusses integer programming problems and the branch-and-bound method for solving them.  If time permits, nonlinear models are briefly discussed.