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課程名稱 |
確定型模式與方法
DETERMINISTIC MODELS AND METHODS |
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開課學期 |
96-1 |
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授課對象 |
工學院 機械工程學系 |
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授課教師 |
周雍強 |
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課號 |
IE5036 |
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課程識別碼 |
546 U6060 |
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班次 |
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學分 |
3 |
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全/半年 |
半年 |
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必/選修 |
選修 |
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上課時間 |
星期五2,3,4(9:10~12:10) |
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上課地點 |
國青233 |
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備註 |
機械系大學部學生選修不計入系選修學分與吳政鴻合開
總人數上限：25人
外系人數限制：10人 |
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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 |
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課程大綱
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課程概述 |
The complete title of this course is: Deterministic Models and Methods for Production Systems Engineering
Over the last two decades, the globalization trend has brought about vibrant supply, demand and engineering chains of production. These systems are dynamic in their evolution, configuration and operation. At the same time, large scale, complex factories have been developed. In this course, we will discuss mathematical tools for analysis and optimization of production by factory and collaborative enterprise chain. This course will cover linear programming, unconstrained optimization, stochastic linear programming, non-linear programming, integer programming, and dynamic system optimization. We will use example problems in production systems engineering and industrial economics to develop in-depth understanding of the theory. |
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課程目標 |
The objective of this course is to develop mathematical sophistication that is required in research work in production systems engineering and industrial economics. Students will learn how to model problems and optimize solutions in resource configuration, product portfolio planning, competition game, manufacturing strategy, and risk control. |
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課程要求 |
Pre-requisites: Operations Research, Calculus, Linear Algebra.
This course covers materials that are more advanced than what is usually found in introductory operations research courses. Proofs of basic theorems in linear programming will be covered to establish solid foundation for other topics. As a pre-requisite, students are expected to have good grasp of vector spaces. |
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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; Dynamic programming and optimal control, Dimitri P. Bertsekas, 2nd edition, Chapter 4. |
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評量方式
(僅供參考) |
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No. |
項目 |
百分比 |
說明 |
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1. |
Homework |
40% |
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2. |
Mid-term exam |
25% |
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3. |
Final exam |
25% |
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4. |
Term paper |
10% |
a group project work |
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週次 |
日期 |
單元主題 |
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第1週 |
9/21 |
Introduction |
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第2週 |
9/28 |
Vector space and linear systems of equations |
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第3週 |
10/05 |
Linear programming |
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第4週 |
10/12 |
Duality |
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第5週 |
10/19 |
Duality and Sensitivity |
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第6週 |
10/26 |
Stochasic linear programming |
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第7週 |
11/02 |
Unconstrained optimization |
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第8週 |
11/09 |
Unconstrained optimization |
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第9週 |
11/16 |
Mid-term exam |
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第10週 |
11/23 |
Non-linear programming (by Prof. Wu) |
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第11週 |
11/30 |
Non-linear programming (by Prof. Wu) |
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第12週 |
12/07 |
Non-linear programming (by Prof. Wu) |
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第13週 |
12/14 |
Integer programming (by Prof. Wu) |
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第14週 |
12/21 |
Dynamic systems modeling |
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第15週 |
12/28 |
Dynamic optimization |
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第16週 |
1/04 |
Optimal control |
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第17週 |
1/11 |
Term paper |
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第18週 |
1/18 |
Final exam |
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