Course detail
Mathematical Methods in Logistics
FSI-SMA-A Acad. year: 2026/2027 Summer semester
Supervisor
Department
Learning outcomes of the course unit
Prerequisites
Planned learning activities and teaching methods
Assesment methods and criteria linked to learning outcomes
Credit will be awarded for the completion of a semester project. This will involve the independent development of a genetic algorithm for solving a combinatorial optimization problem in logistics. The exam will take the form of a project defense, which will be assigned no later than the 10th week of the semester.
Language of instruction
English
Aims
Specification of controlled education, way of implementation and compensation for absences
The study programmes with the given course
Programme N-LAN-A: Logistics Analytics, Master's
branch ---: no specialisation, 5 credits, compulsory
Type of course unit
Lecture
26 hours, optionally
Syllabus
Week 1-3: Introduction to convex optimisation, convex functions, convex sets
Week 4-5: Quadratic programming
Week 6- 9: Evolutionary algorithms with an emphasis on genetic algorithms
Week 10-13: Implementation techniques and algorithm design for solving the so-called Green TSP problem
Exercise
13 hours, compulsory
Syllabus
In the first exercise we recall elementary notions from analytical geometry and numerical methods. Tutorial examples will be calculated. Further exercises will topically follow the lectures from the previous week.