MAT-INF4110 – Mathematical Optimization
Course description
Course content
The course treats selected topics in convexity, optimization and matrix theory. Possible topics include: combinatorial optimization, combinatorial matrix theory, convex analysis, and convex optimization. Usually the version with combinatorial optimization and matrix theory, convexity and polyhedral theory, and also an introduction to polyhedral combinatorics.
Learning outcome
The goal of this course is for students to:
- have knowledge of basic convex analysis and combinatorial optimization
- understand the basic theory of polyhedra and polytopes
- know basic theory combinatorial matrix theory and network flows
- be able to develop algorithms, exact and approximate for some types of combinatorial optimization
Admission
Students who are admitted to study programmes at UiO must each semester register which courses and exams they wish to sign up for in Studentweb.
If you are not already enrolled as a student at UiO, please see our information about admission requirements and procedures.
Prerequisites
Recommended previous knowledge
MAT2400 – Real Analysis, MAT-INF1100 – Modelling and Computations (discontinued), MAT-INF3100 – Linear Optimization (continued).
Overlapping courses
- 10 credits overlap with MAT-INF9110 – Mathematical Optimization (discontinued)
- 10 credits overlap with INF-MAT5360 – Mathematical optimization (discontinued)
- 10 credits overlap with INF-MAT9360 – Mathematical Optimization (discontinued)
The information about overlaps is not complete. Contact the Department for more information if necessary.