Course syllabus


FMAN60, 6 credits, A (Second Cycle)

Valid for: 2020/21
Decided by: PLED F/Pi
Date of Decision: 2020-04-01

General Information

Main field: Technology.
Elective Compulsory for: I3
Elective for: BME4, D4-mai, E4, F4, F4-bs, F4-bg, F4-fm, F4-r, F4-mai, M4, Pi4-bs, Pi4-fm, Pi4-bem, Pi4-bam
Language of instruction: The course will be given in English on demand


The aim of the course is to present basic optimization theory, and to give an overview of the most important methods and their practical use.

Learning outcomes

Knowledge and understanding
For a passing grade the student must

Competences and skills
For a passing grade the student must


Quadratic forms and matrix factorisation. Convexity. The theory of optimization with and without constraints: Lagrange functions, Kuhn-Tucker theory. Duality. Methods for optimization without constraints: line search, steepest descent, Newton methods, conjugate directions, non-linear least squares optimization. Methods for optimization with constraints: linear optimization, quadratic programming, penalty and barrier methods.

Examination details

Grading scale: TH - (U,3,4,5) - (Fail, Three, Four, Five)
Assessment: Written test comprising theory and problems. Two computer exercises and one project.

The examiner, in consultation with Disability Support Services, may deviate from the regular form of examination in order to provide a permanently disabled student with a form of examination equivalent to that of a student without a disability.

Code: 0117. Name: Optimization.
Credits: 6. Grading scale: TH.
Code: 0217. Name: Computer Programming.
Credits: 0. Grading scale: UG.


Assumed prior knowledge: Basic university studies in calculus and linear algebra, including basic theory of quadratic forms.
The number of participants is limited to: No
The course overlaps following course/s: FMA051, MATC51

Reading list

Contact and other information

Course coordinator: Studierektor Anders Holst,
Course administrator: Studerandeexpeditionen,
Teacher: Stefan Diehl,
Course homepage: