TAOP88 · 6 credits · Basic level (G2F) · Matematik, Tillämpad matematik
Engineering Optimization
Active · next start HT 2026
77%
passed the latest ordinary exam
TEN1 · 24 Mar 2026 · 73 students
82%
passed the ordinary exams, all sittings over the last 5 years
TEN1 · 806 students
69%
Harder than 69% of courses at basic level
Compared with 874 courses at the same level, ordinary exams over the last three academic years. 270 students.
Part of 5 programmes
Exam
TEN1 Written examination
- 5
- 4
- 3
- U
Ordinary exams
82% passed · 806 students
- 77%73
- 65%55
- 61%71
- 68%71
- 92%95
- 84%94
- 95%78
- 89%99
- 90%61
- 89%109
Re-exams
66% passed · 191 students
- 13%8
- 39%18
- 67%12
- 33%6
- 79%28
- 65%17
- 67%6
- 67%18
- 71%17
- 75%8
- 100%13
- 79%14
- 69%13
- 69%13
- Pass the re-exam: 66% (191 students), compared with 82% (806 students) on the ordinary exam
- Get 4 or 5: 42% (997 students)
Show small sittings (2)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 50%4
- 75%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
Main rounds
100% passed · 656 students
- 100%63
- 100%54
- 100%52
- 100%76
- 100%86
- 100%73
- 100%106
- 100%41
- 100%105
Later rounds
100% passed · 86 students
- 100%5
- 100%9
- 100%28
- 100%10
- 100%6
- 100%5
- 100%6
- 100%7
- 100%5
- 100%5
- Pass a later round: 100% (86 students), compared with 100% (656 students) on the ordinary exam
Show small sittings (58)
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
The course deals with mathematical tools for formulating, solving and analyzing optimization problems that engineers may encounter. Sustainable development and environmental aspects are prominent aspects in the applications that are discussed. Focus lies on the engineering aspect of building a toolbox with different methods for different problems, and choosing the best method for each problem type. The algorithms are intended to be suitable for large scale problems and implementation on computer. After finishing the course, the student shall be able to:
- formulate optimization problems as effective mathematical models
- explain the design of and the principles behind efficient solution methods and choose and use the methods for solving different types of optimization problems
- use available software for solving optimization problems
- explain and use basic concepts, such as local and global optimality, convexity, extreme point, duality, heuristic, branch-and-bound, cutting planes, and basic graph theory, especially trees and cycles of different kinds
- develop heuristics for certain structured optimization problems
- use optimality conditions for certain optimization problem to determine the optimality of a given solution
- give examples of how optimization can be used to promote sustainable development and improve the environment
Content
Fundamental concepts and tools for solving optimization problems, such as mathematical modelling, optimality conditions, convexity, sensitivity analysis, duality, and some graph theory. Basic methods for linear, nonlinear, integer and network optimization.Heuristics for hard combinatorial optimization problems. Examples onapplications that are relevant for engineers and that concern different aspects within sustainable development.
- Examiner
- Björn Morén
- Scheduled hours
- 54 h
- Main field of study
- Matematik, Tillämpad matematik