TNK090 · 6 credits · Basic level (G2F) · Matematik, Tillämpad matematik, Transportsystem
Queueing Theory
Active · next start HT 2026
67%
passed the latest ordinary exam
TEN1 · 12 Jan 2026 · 21 students
48%
passed the ordinary exams, all sittings over the last 5 years
TEN1 · 84 students
Unusually easy in 2025/26
67% passed the ordinary exam in 2025/26 (21 students), against 39% on average in earlier years (63 students).
Part of 1 programme
Exam
TEN1 Written examination
- 5
- 4
- 3
- U
Ordinary exams
48% passed · 84 students
- 67%21
- 53%19
- 25%12
- 43%21
- 36%11
Re-exams
26% passed · 57 students
- 40%5
- 11%9
- 0%5
- 60%5
- 33%6
- 13%8
- 17%12
- 57%7
- Pass the re-exam: 26% (57 students), compared with 48% (84 students) on the ordinary exam
- Get 4 or 5: 16% (141 students)
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.
- 33%3
- 67%3
- 67%3
Other modules
Partial exams, hand-ins and labs. They are not part of the figures at the top.
Hand-in or lab
UPG1 Project
- G
- U
Main rounds
81% passed · 32 students
- 100%21
- 45%11
Later rounds
95% passed · 40 students
- 100%18
- 100%16
- 67%6
- Pass a later round: 95% (40 students), compared with 81% (32 students) on the ordinary exam
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.
- 100%2
About the course
Aim
The aim of the course is give a working knowledge of queuing models, a description of the underlying theory and examples of their applications in the area of communication and transport.
- construct models in discrete and continuous time based on Markov Chains
- describe and explain the theory of Markov Chains
- describe and motivate Little's formula and its applications
- describe and analyze basic Markov queuing models and situations to which they may be applied
- apply Markov models for selected applications
- construct and analyze priority queuing systems
- describe networks of queuing systems
Content
The Poisson process, Discrete time and continuous time Markov Chains. Markov queuing systems: one server, several servers, finite and infinite carrying capacity, Markovian queuing systems, networks of queuing systems, M/M/, M/M/m, M/G/1 systems, Theory and methods applied to applications in communication, traffic and transport systems.
- Examiner
- Johan M Karlsson
- Scheduled hours
- 38 h
- Main field of study
- Matematik, Tillämpad matematik, Transportsystem