Selected Topics in Optimization

Postgraduate course

Course description

Objectives and Content

Objectives: The course aims to give knowledge in the selected optimization topics.

Content: The course deals with optimization theory and algorithms. Exact content wil vary from year to year.

Learning Outcomes

On completion of the course the student should have the following learning outcomes defined in terms of knowledge, skills and general competence:



The student

  • knows the theory of the selected optimization topics that have been lectured

ECTS Credits


Level of Study


Semester of Instruction

Required Previous Knowledge
At least 120 ECTS in computer science, preferably including some mathematics
Recommended Previous Knowledge
Good knowledge to optimization.
Access to the Course
Access to the course requires admission to a master's programme at The Faculty of Mathematics and Natural Sciences
Teaching and learning methods

The teaching is given in terms of lectures

Lectures / 2-4 hours per week

Forms of Assessment
Final oral exam
Grading Scale
The grading scale used is A to F. Grade A is the highest passing grade in the grading scale, grade F is a fail.
Assessment Semester
Same semester the course is taught, and the subsequent.
Reading List
The reading list will be available within July 1st for the autumn semester and December 1st for the spring semester
Course Evaluation
The course will be evaluated by the students in accordance with the quality assurance system at UiB and the department
Examination Support Material
Programme Committee
The Programme Committee is responsible for the content, structure and quality of the study programme and courses.
Course Coordinator
Course coordinator and administrative contact person can be found on Mitt UiB, or contact Student adviser
Course Administrator
The Faculty of Mathematics and Natural Sciences represented by the Department of Informatics is the course administrator for the course and study programme.