TAOP52 · 4 credits · Basic level (G1F) · Matematik, Tillämpad matematik
Introduction to Operations Research
Active · next start VT 2027
66%
passed the latest ordinary exam
TEN1 · 29 May 2026 · 219 students
62%
passed the ordinary exams, all sittings over the last 5 years
TEN1 · 1,047 students
71%
Harder than 71% of courses at basic level
Compared with 874 courses at the same level, ordinary exams over the last three academic years. 460 students.
Part of 1 programme
Exam
TEN1 Written examination
- 5
- 4
- 3
- U
Ordinary exams
62% passed · 1,047 students
- 66%219
- 66%241
- 70%207
- 44%202
- 66%178
Re-exams
55% passed · 498 students
- 67%51
- 71%24
- 61%77
- 31%26
- 57%56
- 67%27
- 60%86
- 59%49
- 28%57
- 44%45
- Pass the re-exam: 55% (498 students), compared with 62% (1,047 students) on the ordinary exam
- Get 4 or 5: 12% (1,545 students)
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Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
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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
Main rounds
100% passed · 885 students
- 100%193
- 100%203
- 100%150
- 100%174
- 100%165
Later rounds
100% passed · 6 students
- 100%6
- Pass a later round: 100% (6 students), compared with 100% (885 students) on the ordinary exam
Show small sittings (30)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
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About the course
Aim
Within optimization theory, mathematical theories and methods are treated that aim to analyze and solve decision problems that arise in technology, economics, medicine, etcetera. The course provides, together with the continuation course TAOP62, a broad orientation to optimization theory, but a focus on basic theory and methods for continuous optimization problems in finite dimension, as well as an insight into its application to analyze practical optimization questions.
After completing the course, the student should be able to:
- M1 (Modelling):identify questions of an optimization nature in order to construct mathematical models for simpler optimization problems.
- M2 (Theory and Method):use the basic concepts and theorems described by the course content, as well as choose and apply appropriate methods in order to solve commonly occurring optimization problems.
- M3 (Accounting):argue for their approaches using relevant concepts within the course, and present clear calculations and reasoning.
- M4 (Software):use available optimization software to solve standard optimization problems.
Content
- General optimality concepts: Basic convexity theory for functions and sets, optimality conditions, local and global optima, relaxation and restriction.
- Linear programming: Linear optimization models with continuous decision variables, graphical solution, mathematical theory of linear programming, the simplex method, duality, sensitivity analysis.
- Nonlinear programming: Nonlinear optimization models continuous decision variables, with/without subconditions, steepest slope method, Newton's (modified) method, exact line search, interval bisection, the Karush-Kuhn-Tucker conditions.
- Examiner
- Nils-Hassan Quttineh
- Scheduled hours
- 44 h
- Main field of study
- Matematik, Tillämpad matematik