Course details
Quantitative Risk Management Using Robust Optimization
MATH 80624A
More specifically, students will become familiar with the main tools that are used in the application of the robust optimization paradigm: convex theory, data-driven uncertainty sets design, adjustable decision rules, tractable reformulation, and decomposition algorithms for problems of infinite size. The course will also cover a set of practical applications where the use of such tools is called-for. Applications will be inspired from a diversified range of fields of practice.
Themes covered
1) Why is there a recent surge of interest in robust optimization?
2) Robust counterpart of Linear Programs
3) Data-driven Uncertainty Set Design
4) Robust Nonlinear Programming
5) Adjustable Robust Linear Programming
6) Value of Flexibility Using Tractable Decision Rules
7) Globalized Robust Counterparts
8) Distributionally Robust Optimization
9) Robust Markov Decision Processes
10) Robust Preference Optimization
11) Pareto Robust Optimization
12) A Survey of Recent Applications
Course code
MATH 80624A
Subject
Mathématiques
Program
PhD
Location
Côte-des-Neiges
Instruction mode
On-site learning
Credits
3