Course Description
Linear optimization (or linear programming) is the most important branch of optimization, with applications to several areas such as chemistry, computer science, defence, finance, public policy, scheduling, telecommunications, transportation, and many others. This course will provide an integrated view of the theory, solution techniques, and applications of linear optimization. The treatment of most topics will begin with a geometric point of view, followed by the development of the solution techniques (algorithms), which are described using linear algebra. A background in linear algebra and multivariate calculus is assumed. Topics covered include linear programming formulations, geometry of linear programming, the simplex method, duality, sensitivity analysis, interior point methods, and integer programming basics. Apart from problems involving proofs (in homework and exams), the student will use MATLAB for implementing some calculations and algorithms. A state-of-the-art modeling software (AMPL) will also be introduced for solving real-life examples.

Syllabus
Tentative Course Schedule

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