Course content

Finite dimensional theory for extrema with and without constraints. Convexity. Brief review of linear optimization and duality. Functionals, functional derivatives, and variational calculus. Central algorithms and applications.

Learning outcome

The students shall know basic analytical and numerical methods in optimization.

Learning methods and activities

Lectures, exercises and mid-term examination. Portfolio assessment is the basis for the grade awarded in the course. This portfolio comprises a written final examination 80% and the midterm assignment 20%. The results for the constituent parts are to be given in %-points, while the grade for the whole portfolio (course grade) is given by the letter grading system. The midterm examination will only count in a positive direction. If the result of the midterm examination is poorer then the result in the final exam, the final grade will be based on the written examination only. Retake of examination may be given as an oral examination. Lectures will be given in English if international master or exchange students want to attend the course.

Compulsory assignments

• Exercises and projects

Recommended previous knowledge

The course is based on the courses Calculus 1-4, or equivalent. TMA4145 Linear methods, or equivalent.

Course materials

Will be announced at the start of the course.

Credit reductions