Mathematics 353 - ADV TOPICS DISCRETE APP MATH

Topics course. A senior-level course in Mathematical Optimization. Develops geometric and algebraic views of linear programming in parallel. Proof-based treatment of the Simplex Algorithm and LP Duality. Introduction to classical models in combinatorial optimization (including problems in networks and scheduling). Also covers: modeling logical constraints, integer programming for NP-hard problems, branch-and-bound algorithm, integrality gap, specialized algorithmic methods, dynamic programming, intro to provably-good approximation, and intro to rigorous notions of efficiency. Course is lecture-based, and includes weekly homework, regular computational lab sessions, two exams, and a final presentation (which connects to the applied optimization literature). Prerequisites: Linear Algebra (Math 211), Discrete Mathematics (Math 153) or similar, and preferred: some previous exposure to computing (either a software like Matlab, R, SPSS, Excel, etc, or a coding language like Java, Python, etc).

Topic: Optimization.