Integer Programming and Combinatorial Optimization
A graduate-level MIT OpenCourseWare course covering the theory, algorithms, and applications of integer optimization. The syllabus runs in four parts: formulating and relaxing integer programs, the algebra and geometry underlying integer optimization (polyhedral theory, valid inequalities), algorithms including branch and bound, cutting planes, and Lagrangian relaxation, and extensions such as robust and stochastic integer optimization. Materials include lecture notes, problem sets, and exams drawn from the MIT Sloan and EECS curriculum, taught to students already familiar with linear programming and linear algebra. There is no video lecture series; the course is delivered as a full set of downloadable readings and assignments, free to access with no certificate offered. It suits anyone wanting a rigorous, self-study path through combinatorial optimization as taught at MIT.