Fundamentals of Optimization

3 Credits

Introduction to theory and algorithms for linear, discrete, and convex mathematical optimization. Significant portion dedicated to linear optimization theory from both geometric and algebraic perspectives. Basic coverage of discrete optimization, including modeling techniques and algorithmic ideas for solving discrete optimization problems such as branch-and-bound and cutting planes. Basic introduction to convex optimization, including convex sets and functions, duality theory, and optimality conditions.