TMA4180 - Optimization 1


Examination arrangement

Examination arrangement: Aggregate score
Grade: Letter grades

Evaluation Weighting Duration Grade deviation Examination aids
School exam 70/100 4 hours C
Portfolio 30/100

Course content

First and second order necessary and sufficient (Karush-Kuhn-Tucker) optimality conditions for unconstrained and constrained optimization problems in finite-dimensional vector spaces. Basics of convex analysis and Lagrangian duality theory and their application to optimization problems and algorithms. An overview of modern optimization techniques and algorithms for smooth problems (including line-search/trust-region, quasi-Newton, interior point and active set methods, SQP). Basic derivative-free and non-smooth optimization methods. Introduction to vector optimization.

Learning outcome

The student successfully meeting the learning objectives of the course will be able to:

  1. assess the existence and uniqueness of solutions to a given optimization problem;
  2. validate convexity of functions, sets, and optimization problems;
  3. derive necessary and sufficient optimality conditions for a given optimization problem;
  4. solve small optimization problems analytically;
  5. explain the underlying principles and limitations of modern techniques and algorithms for optimization;
  6. estimate the rate of convergence and complexity requirements of various optimization algorithms;
  7. implement optimization algorithms on a computer;
  8. apply optimization algorithms to model problems in engineering and natural sciences.

Learning methods and activities

Lectures, exercises and project. The final grade is composed of a written exam (70%) and a portfolio of project work (30%). Lectures will be given in English if international master or exchange students want to attend the course.

Further on evaluation

In order to pass the course, a passing grade (A-E) in the written exam is required. In case of a retake of the course, all the course parts have to be taken again. The re-sit examination for the written exam may be given as an oral examination. There will be no re-sit examination for the portfolio.

If the course is taught in English, the exam will be given only in English. Students are free to choose Norwegian or English for written assessments or the portfolio.

Course materials

Will be announced at the start of the course.

Credit reductions

Course code Reduction From To
SIF5030 7.5

Version: 1
Credits:  7.5 SP
Study level: Second degree level


Term no.: 1
Teaching semester:  SPRING 2024

Language of instruction: English, Norwegian

Location: Trondheim

Subject area(s)
  • Mathematics
  • Technological subjects
Contact information
Course coordinator:

Department with academic responsibility
Department of Mathematical Sciences


Examination arrangement: Aggregate score

Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
Spring ORD School exam 70/100 C 2024-05-08 15:00 INSPERA
Room Building Number of candidates
SL410 Sluppenvegen 14 61
Spring ORD Portfolio 30/100





Room Building Number of candidates
Summer UTS School exam 70/100 C INSPERA
Room Building Number of candidates
  • * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.

For more information regarding registration for examination and examination procedures, see "Innsida - Exams"

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