Degrees incorporating this pedagocial element :
Description
The objective of this course is to present different techniques to handle uncertainty in decision problems. These techniques will be illustrated on several applications e.g. inventory control, scheduling, energy, machine learning.
Syllabus : Introduction to uncertainty in optimization problems; Reminders (probability, dynamic programming, ...); Markov chains; Markov decision processes; Stochastic programming; Robust optimization
Recommended prerequisite
Basic courses in probability and linear programming
Courses offered by :
In brief
Period : Semester 9Credits : 6
Number of hours
- Lectures (CM) : 36h
Hing methods : In person
Location(s) : Grenoble
Language(s) : English
Contact(s)
Program director
Bruno Gaujal
Moritz Muhlenthaler
International students
Open to exchange students