隨機規劃
Stochastic Programming
| 節 | 週三 |
|---|---|
2 09:00–09:50 | 隨機規劃 A904 3 節連堂 |
3 10:10–11:00 | |
4 11:10–12:00 |
* 根據陽明交大上課時間表所列
The aim of the course is to introduce students to the optimization problems with uncertainty. The field of stochastic programming is developing rapidly with the applications to many disciplines, including many decision problems for transportation and logistics. The course will cover an overview of the basic theories, solution methods, real-world applications. This course has a research level orientation and as such, students should be able to review literature on stochastic programming and conduct computational experiments.
Operations Research
Course Material will be on the E3 platform.
1. Class Participation: 20% 2. Midterm exam: 40% 3. Final project (presentation & written report): 40%
- Mathematical Modeling Background
- Stochastic Linear Programs
- Sampling and Monte Carlo Methods
- Computational/Decomposition Methods
- Chance Constraints
- Stochastic Integer Programming
- Risk Measures
- Stochastic Programming Application Cases
- Examinations & Projects
| 週次 | 主題 |
|---|---|
| 第 1 週 | Basic stochastic programming modeling concepts |
| 第 2 週 | Review of mathematical programming models |
| 第 3 週 | Formulating the deterministic equivalent of stochastic programs |
| 第 4 週 | Basic theory and properties of two-stage stochastic linear programming with recourse |
| 第 5 週 | Extensions to the problems with multiple stages |
| 第 6 週 | Exterior sampling methods for large scale problems |
| 第 7 週 | Statistical inferences; Variance reduction techniques |
| 第 8 週 | The L-Shaped method |
| 第 9 週 | Multi-cut methods; Stabilizing the L-Shaped method |
| 第 10 週 | Basic theory of probabilistic constraints |
| 第 11 週 | Sampling methods for approximating chance constraints |
| 第 12 週 | Stochastic Integer Programming |
| 第 13 週 | Dispersion statistics; Coherent risk measures |
| 第 14 週 | Prelim Examination |
| 第 15 週 | SP applications in transportation |
| 第 16 週 | SP applications in logistics management |
| 第 17 週 | Final project presentation |
| 第 18 週 | Final project report |
Reference Books: 1. Birge, J. R. and Louveaux, F. (2011). Introduction to stochastic programming. Springer. 2. A. Shapiro, D. Dentcheva and A. Ruszczynski, Lectures on Stochastic Programming: Modeling and Theory, SIAM, Philadelphia, 2009. 3. A. Ruszczynski and A. Shapiro (Eds.), Stochastic Programming. Handbooks in Operations Research and Management Science Volume 10. New York, NY, 2003.
- 地點
- TBA
- 時間
- TBA
- 聯絡方式
- TBA