Course detail
Mathematical Methods in Logistics
FSI-SMA-AAcad. year: 2026/2027
The subject is focused on selected optimization tasks. Attention will be paid in particular to the tasks of convex optimization, calculus of variations and the basics of optimal control.
Language of instruction
Number of ECTS credits
Assignment to study programme types
Mode of study
Guarantor
Department
Entry knowledge
Knowledge of foundations of the following topics is required:
- differential and integral calculus of one-variable functions
- vector and matrix calculus
- numerical optimisation
- probability
Rules for evaluation and completion of the course
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.
Aims
Study aids
Prerequisites and corequisites
Basic literature
M. H. Veatch, Linear and Convex Optimization: A Mathematical Approach, Wiley, [2021]. (EN)
W. Forst and D. Hoffmann, Optimization―Theory and Practice, Springer Undergraduate Texts in Mathematics and Technology, 2010th Edition, [2010]. (EN)
Recommended reading
Classification of course in study plans
Type of course unit
Lecture
Teacher / Lecturer
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
Teacher / Lecturer
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.