Combinatorial Optimization OpenCourseWare: MIT's Free Online PH.D. Level Course on Combinational Optimization
'Topics in Combinatorial Optimization,' a graduate-level OpenCourseWare offered by the Massachusetts Institute of Technology, focuses on the use of combinatorics to solve complex problems in mathematics, finance, economics and other fields. The course is intended for graduate students and professionals interested in learning the applications of this challenging and versatile field of study.
Topics in Combinatorial Optimization: Course Specifics
| Degree Level | Free | Audio | Video | Downloads |
|---|---|---|---|---|
| Graduate | Yes | No | No | Yes |
| Lectures/Notes | Study Materials | Tests/Quizzes |
|---|---|---|
| Yes | Yes | No |
Topics in Combinatorial Optimization: Course Description
Combinatorial optimization involves the use of algorithms to solve complex problems in nearly every sector of the economy, including finance, marketing, production, distribution, and engineering and information technology. The associated techniques are employed to find feasible, as well as the optimal solutions to problems while making efficient use of all available resources, including labor, capital and materials. 'Topics in Combinatorial Optimization' is a free course that is taught by Professor Michel Goemans of the MIT Department of Mathematics. This course covers a wide variety of topics, including jump emphasis, matroid union, non-bipartite matching with emphasis on the Tutte-Berge formula and Gallai-Edmonds decomposition. Students will study a variety of theories, including the Gallai-Milgram and Bessy-Thomasse theorems on partitioning graphs by directed paths and cycles. There is also a review of cyclic orderings, the cyclic stable set polytope, the Posets and Dilworth Theorem and multiflow and disjoint path problems. The primary focus of this course is to prepare students with the knowledge and skills necessary for developing combinatorial solutions to complex real-world problems.
The materials for this course include downloadable lecture notes, assignments and a reading list. If you are interested in taking this course, go to the combinational optimization course page.
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