Tentalabbet

TNK049 · 6 credits · Basic level (G2F) · Matematik, Tillämpad matematik

Optimization

Active · next start HT 2026

26%

passed the latest ordinary exam

TEN1 · 18 Mar 2026 · 19 students

33%

passed the ordinary exams, all sittings over the last 5 years

TEN1 · 165 students

Unusually hard in 2025/26

21% passed the ordinary exam in 2025/26 (42 students), against 37% on average in earlier years (123 students).

Part of 1 programme

Exam

TEN1 Written examination

  • 5
  • 4
  • 3
  • U

Ordinary exams

33% passed · 165 students

  • 26%19
  • 17%23
  • 25%8
  • 38%16
  • 15%13
  • 27%22
  • 62%13
  • 31%16
  • 42%12
  • 52%23

Re-exams

46% passed · 37 students

  • 43%14
  • 14%7
  • 78%9
  • 43%7
  • Pass the re-exam: 46% (37 students), compared with 33% (165 students) on the ordinary exam
  • Get 4 or 5: 7% (202 students)
Show small sittings (1)

Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.

  • 25%4

Other modules

Partial exams, hand-ins and labs. They are not part of the figures at the top.

Hand-in or lab

LAB1 Laboratory work

  • G
  • U

Main rounds

100% passed · 74 students

  • 100%12
  • 100%15
  • 100%22
  • 100%13
  • 100%12

Later rounds

100% passed · 6 students

  • 100%6
  • Pass a later round: 100% (6 students), compared with 100% (74 students) on the ordinary exam
Show small sittings (3)

Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.

  • 0%4
  • 100%2
  • 100%2

About the course

Aim

The course provides basic insights in optimization, especially optimization of linear and nonlinear (continuous) problems and problems with a network structure. After completing the course, the student should be able to:

Content

  • Linear programming: Modeling, basic mathematical theory and geometry, the simplex method, sensitivity analysis, duality, optimality conditions.
  • Nonlinear optimization: Modeling, convexity, unconstrained optimization, linearly constrained optimization, optimality conditions.
  • Network optimization: Modeling, tree problems, path problems, versions of the minimum cost flow problem and the simplex method applied to problems with network structure.
Examiner
Stefan Engevall
Scheduled hours
48 h
Main field of study
Matematik, Tillämpad matematik
Syllabus on Studieinfo ↗