最佳化方法與應用
Optimization Methods and Applications
| 節 | 週二 |
|---|---|
2 09:00–09:50 | 最佳化方法與應用 MB311 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
This course aims to introduce the theory and potential applications of computational optimization. Fundamentals in management science and optimization to address include integer programming models, simplex method and duality theory, network models, dynamic programming, branch-and-bound, and meta-heuristics and evolutionary computing. Real applications and success stories will be specially highlighted along each subject to envision the use of optimization methods in managerial decisions.
Prerequisite: Computer Programming
1.Homework and Assignments, Exams and Quizzes, Evaluation and Grading Policy: Assignments (including programming) 30%; Mit-term exam 30%; Final Project 30%; Participation 10%. 2. Pedagogy and other supplementary information (websites, TAs, handouts and/or databases):
1.Homework and Assignments, Exams and Quizzes, Evaluation and Grading Policy: Assignments (including programming) 30%; Mit-term exam 30%; Final Project 30%; Participation 10%. 2. Pedagogy and other supplementary information (websites, TAs, handouts and/or databases):
| 週次 | 主題 |
|---|---|
| 第 1 週 | Introduction |
| 第 2 週 | Modeling in (integer) linear programs (Modeling with Gurobi) |
| 第 3 週 | Simplex Method |
| 第 4 週 | Duality and Sensitivity Analysis (Interpretations of Outputs) |
| 第 5 週 | Stable Marriage Problem, Networks Models (transportation, assignment problem) |
| 第 6 週 | Branch-and-Bound Algorithms |
| 第 7 週 | Branch-and-Bound Algorithms |
| 第 8 週 | Mid-term Exam |
| 第 9 週 | Dynamic Programming |
| 第 10 週 | Dynamic Programming |
| 第 11 週 | Dynamic Programming |
| 第 12 週 | Sequential decision analytics and modelling |
| 第 13 週 | Sequential decision analytics and modelling |
| 第 14 週 | Sequential decision analytics and modelling |
| 第 15 週 | Sequential decision analytics and modelling |
| 第 16 週 | Term project Presentation |
Textbooks and Materials: 1. Hillier, F.S. and Lieberman, G.J., Introduction to Operations Research, 11th Ed., McGraw-Hill, 2021, New York. 2. Warren B. Powell (2022), Sequential Decision Analytics and Modeling: Modeling with Python, Boston-Delft: now publishers, http://dx.doi.org/10.1561/9781638280835 3. Articles selected from Operations Research and INFORMS Journal on Applied Analytics
- 地點
- Mabc-MB311[GF]
- 時間
- Mabc-MB311[GF]
- 聯絡方式
- Mabc-MB311[GF]