Study plan for MAMN-INFOP Optimization, fall 2024

Name of qualification

Master of Science in Informatics - Optimization

ECTS Credits

Two years of full-time study, where the normal workload for a full-time student is 60 credits for one academic year.



Language of Instruction



Autumn and spring

Objectives and content

Companies in Bergen and the rest of Norway optimize: Manufacturers maximize their profit and minimize the costs of their production processes. Transporters seek to find the fastest driving routes. Investors try to compose portfolios with low risks and high expected returns. Ship brokers engage underwriters to create insurances with a smallest possible premium.

Only good optimizers can optimize well, and only well-designed computer algorithms can do the heavy calculations required in challenging optimization processes. In the master's programme in optimization at Department of Informatics, you will learn how to write and implement such algorithms, and learn how to apply them in practice, so that you will become one of the experts who undertake important real-world optimization tasks.

Required Learning Outcomes

A candidate who has completed his or her qualifications should have the following learning outcomes defined in terms of knowledge, skills and general competence:


The candidate

  • can apply theory and methods of optimization to model and solve real-life problems, within areas such as:

    • Supply chain, logistics and transportation,
    • mathematical finance, and
    • engineering.
  • can explain methodologies and algorithms in optimization and knows how to implement them.
  • has a broad knowledge of the main concepts in optimization.


The candidate

  • can formulate practical problems from industry as optimization problems.
  • is able to plan, design and develop an independent research project in optimization.
  • can suggest or develop suitable techniques for solving optimization problems.
  • can analyze optimization problems and algorithms.
  • can develop and implement suitable techniques for solutions on a computer.

General competence:

The candidate

  • has a sound theoretical and computational basis for further studies in theory, methodologies and software in optimization.
  • is able to work independently and in groups with others.
  • has a critical and analytical view of his/her own work and that of others.
  • can demonstrate an understanding of and respect for scientific values about openness, precision, reliability and the importance of differentiating between knowledge and opinions.

Admission Requirements

The master's programme builds on a bachelor's degree from the Department of Informatics, or a bachelor's degree and at least 80 ECTS of Mathematics and Informatics/Computer science.

Bachelor's degrees from UiB that qualify:

  • Bachelor's degree from Department of Informatics, UiB (BAMN-BINF, BAMN-DSIK, BAMN-DTEK, BAMN-DVIT, BATF-IMØ, BAMN-INF)
  • Bachelor's degree in Information and Communication Technology (IKT) with at least 15 ECTS (at least two courses for at least 7,5 ECTS each) of elective Mathematics
  • Bachelor's degree in Cognitive Science (BASV-KOGNI) with specialization in Informatics
  • Bachelor's degree in Artificial Intelligence (BASV-AIKI) qualifies, if you have at least 80 ECTS of Mathematics and Informatics/Computer Science. Out of these 80 ECTS, at least 40 ECTS must be in Informatics/Computer science, and at least 15 ECTS must be in Mathematics. One course in Statistics can count towards Mathematics (except STAT100). MNF130 and equivalent counts as Informatics. INF-courses and INFO-courses with credit reduction towards INF-courses count as informatics.

Bachelor's degrees that qualify

  • Bachelor's degree in Computing from HVL (Western Norway University of Applied Sciences)
  • Bachelor's degree in Information Technology from HVL
  • Bachelor's degree in Communication Systems from HVL

Other bachelor's degrees might qualify if you have at least 80 ECTS of Mathematics and Informatics/Computer Science. Out of these 80 ECTS, at least 40 ECTS must be in Informatics/Computer science, and at least 15 ECTS (at least two courses with 7,5 ECTS each) must be in Mathematics. If both INF100 and INF109 are part of the Bachelor's degree, the applicant will only get credits for INF100. One course in Statistics can count towards Mathematics (except STAT100). MNF130 (and equivalent) counts as Informatics.

For international self-financing applicants:

The Master's programme is not available for international applicants residing outside of the Nordic countries, the European Union/EEA and Switzerland.

You also need to document:

Compulsory units

The master's programme consists of two components: Coursework of 60 credits and an individual research project (master's thesis) of 60 credits.

Courses: The courses INF234 Algorithms and INF270 Linear Programming are compulsory

In addition, there are 40 credits of elective courses, chosen in agreement with the supervisor.

1. semester autumn: INF234, INF270, MAT261/Elective course

2. semester spring: INF271/Elective course, INF272/Elective course, INF237/Thesis

3. semester autumn: Thesis/Elective course, Thesis

4. semester spring: Thesis

Sequential Requirements, courses

The recommended sequence of the courses in the programme can be found under the heading "Compulsory units".

Study period abroad

You can plan study periods abroad in consultation with your supervisor as a part of the master agreement.

Teaching methods

In preparing your master's thesis you will independently use methods and scientific working techniques from the subject field to research a relevant topic. In some cases, analyses of observation data and data from models are very important in addition to theoretical and experimental studies.

During the 1st semester the student establishes contact with a personal supervisor. Together with the supervisor a subject for the thesis is specified and a schedule is made with an outline of courses and milestones in the thesis work.

A combination of teaching methods is used in the various courses, mainly lectures and groups. You may find more information in the course description.

Assessment methods

The final step in the programme is an oral examination. The examination is held when the master's thesis is submitted, evaluated and approved.

The most common assessment methods in the courses are written and oral examination. The assessment methods for each course are described in the course description.

Grading scale

At UiB the grades are given in one of two possible grading scales: passed/failed and A to F.

The master's thesis will be graded A to F.

The grading scale for each course is given in the course description.

Diploma and Diploma supplement

The Diploma, in Norwegian, and the Diploma Supplement, in English, will be issued when the degree is completed.

Access to further studies

To be eligible for admission to the Doctoral education (PhD) the candidate must have completed a master's degree.

To qualify for the Doctoral education (PhD) at UiB the average grade for the master's thesis, the Master's degree and the bachelor's degree should be at least C.

In order to get enrolled you have to be granted a fellowship for doctoral training.


Information- and communication technology is more and more becoming a basic technology in all kinds of business activity and administration, and our candidates are strongly demanded to maintain and develop IT-systems. Many of the candidates also get employed by the IT-industry or within research and higher education.


The programme will be evaluated according to the quality assurance system of the University of Bergen.

Programme committee

The programme committee is responsible for the academic content, the structure and the quality of the programme. Contact studieveileder@ii.uib.no

Administrative responsibility

The Faculty of Mathematics and Natural Sciences by the Department of Informatics, holds the administrative responsibility for the programme.

Contact information

Please contact the academic adviser for the program if you have any questions: Studierettleiar@ii.uib.no

Phone: + 47 55 58 40 25

The Optimization Research Group: http://www.uib.no/rg/opt