TNSL17 · 6 credits · Basic level (G2F) · Tillämpad matematik, Logistik
Optimization in Logistics
Active · next start HT 2026
100%
passed the latest ordinary exam
TEN1 · 31 Oct 2025 · 8 students
82%
passed the ordinary exams, all sittings over the last 5 years
TEN1 · 61 students
Unusually easy in 2025/26
100% passed the ordinary exam in 2025/26 (8 students), against 81% on average in earlier years (53 students).
Part of 2 programmes
Exam
TEN1 Written examination
- 5
- 4
- 3
- U
Ordinary exams
82% passed · 61 students
- 100%8
- 90%10
- 80%10
- 75%24
- 78%9
Re-exams
No sittings with at least 5 students.
- Get 4 or 5: 41% (61 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.
- 0%1
- 50%2
- 50%2
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 · 44 students
- 100%12
- 100%7
- 100%7
- 100%18
Later rounds
No sittings with at least 5 students.
Show small sittings (6)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 100%4
- 100%2
- 100%4
- 100%2
- 100%2
- 100%2
Hand-in or lab
UPG1 Case study
- G
Main rounds
100% passed · 14 students
- 100%7
- 100%7
Later rounds
100% passed · 21 students
- 100%6
- 100%7
- 100%8
- Pass a later round: 100% (21 students), compared with 100% (14 students) on the ordinary exam
Show small sittings (6)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 100%4
- 100%4
- 100%3
- 100%3
- 100%1
- 100%3
About the course
Aim
The aim of this course is to present a number of application areas within logistics, where quantitative methods are especially suitable.After the course, the students should:
- Understand in which wat more efficient planning in logistics can increase sustainability
- Know and apply basic methods for solving the Traveling Salesman Problem
- Know of different applications, where vehicle routing is an important part
- Know of basic methods for transportation planning and vehicle routing
- Know methods and considerations necessary when doing Strategic Network Planning
- Know and apply basic methods for localization
- Apply construction-, improvement- and the principles behind Tabu search heuristics
- Compute cost allocation using quantitative methods
- Model and solve simple time tabling and scheduling problems
Content
The course contents include:
- Mathematical modeling of Strategic Network Planning (Supply Chain Design)
- Gravitation models for localization
- Location/routing problems
- The Traveling Salesman Problem, and solving it using constraint generation
- Construction heuristics
- Vehicle routing problems, and solving these using heuristics, and by formulating a Set Partitioning Problem
- Scheduling of employees
- Cost allocation using Cooperative Game Theory
- Vehicle routing relating to e-trade
- Principles behind relaxations
- Basic improvement heuristics/local search
- Principles behind Tabu search
- The value of solving relaxed problems
- Examiner
- Stefan Engevall
- Scheduled hours
- 48 h
- Main field of study
- Tillämpad matematik, Logistik