Course Syllabus for

Convex Optimization with Applications
Konvex optimering med tillämpningar

FRT016F, 7.5 credits

Valid from: Autumn 2019
Decided by: FN1/Anders Gustafsson
Date of establishment: 2013-03-03

General Information

Division: Automatic Control
Course type: Third-cycle course
Teaching language: English


The goal of the course is to give students the tools and training to recognize convex optimization problems that arise in applications to present the basic theory of such problems, concentrating on results that are useful in computation to give students a thorough understanding of how such problems are solved, and some experience in solving them to give students the background required to use the methods in their own research work or applications


Knowledge and Understanding

For a passing grade the doctoral student must

Competences and Skills

For a passing grade the doctoral student must

Judgement and Approach

For a passing grade the doctoral student must demonstrate the ability to critically evaluate and compare different formulations of convex optimization problems and different algorithms for different quality criteria

Course Contents

The course has three parts * Basic theory for convex sets and functions * Experience of formulation of application problems as convex optimization problems * Knowledge and experience of efficient optimization algorithms

Course Literature

Boyd, S. & Vandenberghe, L.: Convex Optimization. Cambridge University Press.
Freely available on

Instruction Details

Types of instruction: Lectures, exercises

Examination Details

Examination formats: Written exam, written assignments, miscellaneous. Weekly handin problems Take-home exam Students should take an active role in the weekly exercise sessions
Grading scale: Failed, pass

Admission Details

Assumed prior knowledge: Linera algebra, calculus in several variables, probability theory

Further Information

Replaces FRT015F.

Course Occasion Information

Contact and Other Information

Course coordinator: Emil Vladu <>

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