Graduate Education Institute · Big Data and Business Analytics · Master
Course Objective
This course aims to model and solve complex business and analytics problems using operations research approaches. Core decision and optimization techniques, particularly linear and integer optimization, are addressed within the context of big data and business analytics. The course includes hands-on applications using analytical software on realistic problem scenarios.
Course Content
This course will provide a classification and general overview of quantitative methods used for optimization. Various mathematical programming methods will be explained, and example models will be created for different application areas. Example problems will be modeled and solved using Lingo and Excel Solver.
Core Area Distribution
Teaching Methods
Assessment & Evaluation
ECTS / Workload
| Activity | Quantity | Duration (h) | Total Workload |
|---|---|---|---|
| Course Duration (Including Exam Week) | 14 | 3 | 42 |
| Out of Class Study Period | 14 | 3 | 42 |
| Midterm | 1 | 2 | 2 |
| Quiz | 0 | 0 | 0 |
| Assignment | 2 | 40 | 80 |
| Practice | 0 | 0 | 0 |
| Final | 1 | 2 | 2 |
Course Schedule
| Week | Subject | Preparation |
|---|---|---|
| 1 | Introduction to the Course and Fundamentals of Optimization | Lecture Notes |
| 2 | Introduction to Linear Programming | Lecture Notes |
| 3 | Model Formulation and Problem Definition | Lecture Notes |
| 4 | Graphical Solution Method – Introduction to the Simplex Method | Lecture Notes |
| 5 | The Simplex Method and the Big M Method | Lecture Notes |
| 6 | The Big M Method and the Two-Phase Method | Lecture Notes |
| 7 | Sensitivity Analysis | Lecture Notes |
| 8 | Midterm | Midterm |
| 9 | Using Excel Solver and LINGO (Linear Programming) | Lecture Notes |
| 10 | Integer Programming | Lecture Notes |
| 11 | Applications of Integer Programming | Lecture Notes |
| 12 | Goal Programming | Lecture Notes |
| 13 | Applications of Goal Programming | Lecture Notes |
| 14 | Using Excel Solver and LINGO (Integer Programming and Goal Programming) | Lecture Notes |
| 15 | Literature Presentations | Literature Presentations |
| 16 | Final Exam | Final Exam |