課程名稱 |
確定型模式與方法 Deterministic Models and Methods |
開課學期 |
101-1 |
授課對象 |
工學院 機械工程學系 |
授課教師 |
周雍強 |
課號 |
IE5036 |
課程識別碼 |
546 U6060 |
班次 |
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學分 |
3 |
全/半年 |
半年 |
必/選修 |
選修 |
上課時間 |
星期四6,7,8(13:20~16:20) |
上課地點 |
國青233 |
備註 |
總人數上限:25人 外系人數限制:10人 |
Ceiba 課程網頁 |
http://ceiba.ntu.edu.tw/1011DMM |
課程簡介影片 |
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核心能力關聯 |
核心能力與課程規劃關聯圖 |
課程大綱
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課程概述 |
This course provides an introduction to optimization. It is designed to develop mathematical sophistication that is required in research work in production systems engineering and industrial economics. It covers deterministic models and methods that are useful in solving problems of resource configuration, portfolio and mix planning, supply chain control, scenario-based planning, risk management, operation scheduling, and policy design. It is composed of three parts. In the first part, Linear Programming is discussed at a greater depth than in introductory OR courses, with an emphasis on its geometric interpretation. About half of the semester is devoted to equip students with solid knowledge about Linear Programming and its software tools and applications. In the second part, the knowledge on Linear Programming will be extended to Non-linear Programming, Integer Programming, and Stochastic Linear Programming. In the third part, we will discuss dynamic optimization and optimal control and their application to supply chain control and policy design.
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課程目標 |
This course has dual objectives. For research-oriented students, this course will further develop their mathematical sophistication for advanced graduate courses. For application-oriented students, this course will provide them with solid knowledge about deterministic models and methods and related software tools. The software tool Lindo/Lingo will be used throughout the course to enhance hands-on experience and skills. |
課程要求 |
This course is suitable for both graduate and upper-level undergraduate students with prior knowledge of introductory Operations Research. |
預期每週課後學習時數 |
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Office Hours |
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指定閱讀 |
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參考書目 |
(1)Introduction to Linear Optimization, by Bertsimas and Tsitsiklis, Athena Scientific, 1997, chapters 1, 2 (geometry of LP), 4 (duality), 5 (sensitivity), 10 (IP formulation), 11 (IP methods).
(2)Introduction to Stochastic Programming, by John R. Birge and F. Louveaux, Springer-Verlag, New York, 1997, Chapters 1-4.
(3)Linear and Nonlinear Programming, by Stephen Nash and Ariela Sofer, McGraw-Hill International Edition, 1996. Chapters 2 (fundamentals of optimization), and 10 (unconstrained optimization).
(4)Dynamic Optimization, by Alpha C. Chiang, 1992, McGraw-Hill, Chapters 1, 2, 7, 8. Or, Dynamic programming and optimal control, Dimitri P. Bertsekas, 2nd edition, Chapter 4. |
評量方式 (僅供參考) |
No. |
項目 |
百分比 |
說明 |
1. |
Homework |
40% |
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2. |
Mid-term exam |
30% |
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3. |
Final exam |
30% |
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週次 |
日期 |
單元主題 |
第1週 |
9/13 |
Introduction |
第2週 |
9/20 |
Review Linear algebra |
第3週 |
9/27 |
Linear programming
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第4週 |
10/04 |
Linear programming
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第5週 |
10/11 |
LINGO and application
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第6週 |
10/18 |
Duality
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第7週 |
10/25 |
NLP: KKT conditions
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第8週 |
11/01 |
Integer program: modeling
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第9週 |
11/08 |
Mid Term Exam
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第10週 |
11/15 |
校慶 |
第11週 |
11/22 |
Integer program: methods
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第12週 |
11/29 |
IP Application: setup reduction
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第13週 |
12/06 |
Stochastic linear program
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第14週 |
12/13 |
Linear dynamic systems |
第15週 |
12/20 |
Unconstrained optimization
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第16週 |
12/27 |
Dyamic optimization
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第17週 |
1/03 |
Optimal control
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