隨機規劃
Stochastic Programming
| 節 | 週五 |
|---|---|
2 09:00–09:50 | 隨機規劃 A904（光復） 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 the optimization problems with uncertainty, together with their models and solution techniques. 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, and real-world applications. This course has a research level orientation; therefor, students are expected to review the literature on stochastic programming and conduct some computational experiments.
Operations Research
無備註
E3 Platform
1. Class Participation: 10% 2. Midterm exam: 45% 3. Comprehensive Term Assignment: 20% 4. Final project (presentation & written report): 25%
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| 週次 | 主題 |
|---|---|
| 第 1 週 | Course introduction 9/17 |
| 第 2 週 | Review of mathematical programming models and uncertainty modeling 9/24 |
| 第 3 週 | Basic concepts of stochastic programming modeling 10/1 |
| 第 4 週 | Formulating deterministic equivalent of stochastic programs and general formulations 10/8 |
| 第 5 週 | Typical SP modeling examples 10/15 |
| 第 6 週 | Mathematical representation of EVPI and VSS and their implications 10/22 |
| 第 7 週 | Basic concepts of solution methods and the L-Shaped method 10/29 |
| 第 8 週 | Comprehensive term assignment presentation 11/5 |
| 第 9 週 | Probabilistic programming, Approximation and Sampling Methods 11/12 |
| 第 10 週 | Stochastic integer programming 11/19 |
| 第 11 週 | Multistage SP and dynamic systems 11/26 |
| 第 12 週 | Prelim examination 12/3 |
| 第 13 週 | SP applications in transportation and logistics management 12/10 |
| 第 14 週 | Final project presentation 12/17 |
| 第 15 週 | Final project presentation 12/24 |
| 第 16 週 | National Holiday 12/31 |
| 第 17 週 | Final project report (flexible) 1/7 |
| 第 18 週 | Final project report (flexible) 1/14 |
1. Birge, J. R. and Louveaux, F. (2011). Introduction to stochastic programming. Springer. (Textbook, available on NCTU eBook) 2. A. Shapiro, D. Dentcheva and A. Ruszczynski, Lectures on Stochastic Programming: Modeling and Theory, SIAM, Philadelphia, 2009. (reference) 3. A. Ruszczynski and A. Shapiro (Eds.), Stochastic Programming. Handbooks in Operations Research and Management Science Volume 10. New York, NY, 2003. (reference)
- 地點
- A807
- 時間
- TBA
- 聯絡方式
- kchuang@cc.nctu.edu.tw