MGT 7108 Optimization and Modeling

3 units
Management
Telfer School of Management
This course is designed for students who have already taken courses in optimization and wish to delve deeper. The course will balance providing the theory behind optimization and providing an introduction into methodologies dealing with stochastic, real-world, large scale problems (e.g., decomposition techniques). Topics covered will include convex optimization, stochastic programming, dynamic programming, robust optimization, metaheuristics and machine learning techniques.

Components:

Lecture

Previously Offered Terms:

Winter
All Professors
A Average (8.724)
Most Common: A (66%)
29 students

P

S

NS

F

D

C

B

A-

A+

Jonathan Yu-Meng Li

Winter 2024 - A00

A Average (8.864)
Most Common: A (73%)
22 students

P

S

NS

F

D

C

B

A-

A+

Unknown Professor

Winter 2022 - AV00

A- Average (8.286)
Most Common: A (43%)
7 students

P

S

NS

F

D

C

B

A-

A+