Optimization, 7.5 credits

Learning outcomes

Knowledge and Understanding
After completed studies, the student shall be able to

• account for the fundamental properties of linear and non-linear optimization problems, and
• account for the fundamental properties of the most important methods for solving linear and non-linear optimization problems.

Competence and Skills
After completed studies, the student shall be able to

• formulate an optimization problem from the real world,
• identify different types of optimization problems,
• solve simple optimization problems by hand calculations, and
• apply fundamental numerical methods for solving linear and non-linear optimization problems.

Content

Fundamental concepts in optimization. The formulation of optimization problems. Linear programs with applications. The simplex method. Network problems. Non-linear programming with applications. Non-linear programming with constraints and applications. Programming in Matlab.

Examinations and grades

Theory, 4.5 credits (Code: A001)
Grades used are Fail (F), Sufficient (E), Satisfactory (D), Good (C), Very Good (B) or Excellent (A).

Computer Assignments, 3 credits (Code: A002)
Grades used are Fail (U) or Pass (G).

According to the Higher Education Ordinance, Chapter 6, Section 18, a grade is to be awarded on the completion of a course, unless otherwise prescribed by the university. The university may determine which grading system is to be used. The grade must be determined by a teacher specifically nominated by the university (the examiner).

In accordance with university regulations on grading systems for first and second-cycle courses and study programmes (Vice-Chancellor’s decision ORU 2018/00929), one of the following grades is to be used: fail (U), pass (G) or pass with distinction (VG). For courses included in an international master’s programme (60 or 120 credits) or offered to the university’s incoming exchange students, the A to F grading scale is to be used. The vice-chancellor, or a person appointed by them, may decide on exceptions from this provision for a specific course, if there are special grounds for doing so.

The grades used on this course are Fail (F), Sufficient (E), Satisfactory (D), Good (C), Very Good (B) or Excellent (A).

Comments on grades

The grade for the examination component Theory is given as a grade for the course as a whole, provided that the grade for the examination Computer assignments is Passed.

Modes of assessment

• Theory (code A001): Written examination
• Computer Assignments (code A002): Oral examination

For students with a documented disability, the university may approve applications for adapted or other modes of assessment.

For further information, see the university's local examination regulations.

Specific entry requirements

Mathematical Modelling and Problem Solving, 6 Credits and Foundations of Analysis, 7.5 Credits.

For further information, see the university's admission regulations.

Other provisions

All or parts of the course may be given in English. The teaching methods may be altered, should only a few students take the course.

Students who have been admitted to and registered on a course have the right to receive tuition and/or supervision for the duration of the time period specified for the particular course to which they were accepted (see, the university's admission regulations (in Swedish)). After that, the right to receive tuition and/or supervision expires.

Reading list and other learning resources

Required Reading

Sasane, Amol & Svanberg, Krister
Optimization
Department of Mathematics, Royal Institute of Technology

The compendium Optimization can be purchased at Örebro University.

Additional Reading

Andréasson, Niclas, Evgrafov, Anton, Patriksson, Michael, Gustavsson, Emil, and Nedelková, Zuzana (2016)
An Introduction to Continuous Optimization (third edition)
Studentlitteratur