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Abstract
Hands-on coding-based course on using mathematical optimization methods and software to solve a variety of optimization problems.
Objective
The goal of this course is to learn how to put mathematical optimization theory into practice by using modern mathematical optimization libraries in python. At the end of this course, students should be able to implement algorithms that can tackle a wide variety of mathematical optimization problems.
Content
Key topics include: - Fundamental techniques in applied optimization. - Modeling computational questions in terms of classical mathematical optimization problems, and implementing algorithms to solve these fast.
Resources
Lecture Notes
See moodle page.
Literature
Necessary materials will be provided on moodle.