Facts about the course
- Study points:
- Responsible department:
- Faculty of Logistics
- Lecture Semester:
- Teaching language:
- ½ year
LOG904-131 Applied Dynamic and Stochastic Programming for Logistics (Autumn 2018)
About the course
The course focuses on building of optimization models and on key ideas of selected solution methods that are suitable for applied problems in logistics. Most real-world applications must involve quantitative techniques. Therefore, the course may help students with computational parts of their master theses and with quantitative challenges in their jobs in the future.
Step-by-step, we will follow and develop principal techniques for the cases where uncertainty (e.g. in demand) and time (e.g. planning horizon) must be considered. General outline ¿
Day 1: separability,
Day 2: decomposability,
Day 3: more decision stages,
Day 4: uncertainty by scenarios.
We will study fundamental concepts by using explanatory educational examples to get insight.
Motivating real-world industrial applications will be discussed, which have recently been solved with participation of the lecturer and his colleagues (also from Molde University College).
The lecturer utilizes (and reviews, if necessary) basic concepts from introductory optimization and mathematical courses.
Course participants will work in groups and they will defend submitted results of solved exercises on Day 5 during an oral exam
Lecturer: Pavel Popela, Brno University of Technology, Czech Rep. ( email@example.com )
The course is connected to the following study programs
- Master of Science in Logistics
- Experience-based Master in Logistics
- Master of Science in Petroleum Logistics
- Exchange programme - Master's level
- Form of assessment: Home assessment
- Proportion: 100%
- Duration: -
- Grouping: Group
- Grading scale: Letter (A - F)
- Support material: All printed and written supporting material