Course details
Optimization Models
MATH 20604A
This course provides a hands-on introduction to optimization in business analytics. The objective is learning model formulation, solving problems by programming or using modern solvers, and interpreting results to support decision-making.
The main topics covered in this course include linear and integer programming, network-flow models, multi-objective optimisation, and nonlinear otpimisation models. The course also briefly addresses the issue of uncertainty through stochastic optimisation and the use of heuristic methods. Throughout the course, the emphasis is on concrete examples, typical problem models, and solution implementation.
Themes covered
Linear programming: formulation implementation duality
Network-flow models: structure algorithms applications
Integer programming: use of binary variables linearization solution techniques
Multi-objective optimisation: formulation and trade-offs
Nonlinear optimization: models descent techniques interpretation
Multiperiod models: structure uncertainty treatment decision trees
Heuristics and large-scale optimisation
Important notes
Course in French : MATH 20604
Course code
MATH 20604A
Subject
Mathematics
Program
Bachelor’s degree (BBA)
Location
Côte-des-Neiges
Instruction mode
On-site learning
Credits
3