• In-depth treatment of mixed-integer optimization. Topics include modeling techniques, combinatorial optimization, ideal formulations, cutting plane methods, branching algorithms, row generation algorithms, column generation algorithms, heuristic algorithms, and mixed-integer non-linear optimization. Instruction provided in modeling complex problems arising in practice; understanding the theory of integer optimization; knowing the core technologies employed within modern solvers; and developing algorithms to solve large-scale problems for which off-the-shelf solvers may not be sufficient. Examples drawn from a broad range of industries, such as transportation, energy, telecommunications, finance, product design, sports, and social networks. Includes a term project.

• Textbook Information

There is no information available for this course.