Course detail

Mathematical Methods in Logistics

FSI-SMA-A Acad. year: 2024/2025 Summer semester

Supervisor

doc. Mgr. Petr Vašík, Ph.D.

Department

Institute of Mathematics

Learning outcomes of the course unit

Prerequisites

Knowledge of foundations of the following topics is required:

  • differential and integral calculus of one-variable functions
  • vector and matrix calculus
  • numerical optimisation
  • probability

Planned learning activities and teaching methods

Assesment methods and criteria linked to learning outcomes

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

Programme C-AKR-P: , Lifelong learning
branch CLS: , 5 credits, elective

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: Numerical optimisation methods, Newton's method, gradient descent method and conjugate gradient method
Week 10-13: Variational methods, introduction to optimal control of dynamical systems

Exercise

26 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.