Course details
Fundamentals of Optimization
MATH 60606A
The Simplex algorithm and key optimization principles in Linear Programming are explored, including sensitivity analysis and duality. In Integer Linear Programming, basic concepts, logical relations and their applications are studied, along with branch-and-bound and branch-and-cut algorithms. The Non-Linear Programming section covers convexity and complementary conditions, as well as gradient- and Newton-based algorithms. Finally, foundational concepts of classical heuristics and metaheuristics are introduced. The course develops essential skills for solving complex optimization problems in various fields.
Themes covered
Linear programming
The simplex algorithm
Sensitivity analysis and duality
Integer programming and its applications
Branch-and-bound and branch-and-cut algorithms
Basic notions and algorithms in non-linear programming
Convexity KKT Conditions and Optimality
Gradient- and Newton-based algorithms
Heuristics and metaheuristics
Important notes
Course in French : MATH 60606
Course code
MATH 60606A
Subject
Mathématiques
Program
Maîtrise en gestion (M. Sc.)
Location
Côte-des-Neiges
Instruction mode
On-site learning
Credits
3