課程資訊
課程名稱
作業研究應用與實作
Operations Research Applications and Implementation 
開課學期
114-1 
授課對象
管理學院  資訊管理學系  
授課教師
李家岩 
課號
IM5059 
課程識別碼
725EU3690 
班次
 
學分
3.0 
全/半年
半年 
必/選修
選修 
上課時間
星期二2,3,4(9:10~12:10) 
上課地點
管二304 
備註
本課程以英語授課。
總人數上限:50人 
 
課程簡介影片
 
核心能力關聯
本課程尚未建立核心能力關連
課程大綱
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課程概述

待補This course will provide students to learn the methodologies of operations research and its applications to the real problem. The models include deterministic models (such as linear programming, multi-criteria decision analysis, data envelopment analysis, etc.) and stochastic models (such as Bayesian decision analysis, stochastic programming, Markov decision process, etc.). The course integrates the knowledge domains of the management and engineering, applied in capacity planning, facility layout, supply chain, manufacturing scheduling, performance evaluation, vendor selection and order allocation, Bin-packing, financial investment, etc. We develop the implementation capability of the information system in practice. Finally we should know how to solve the real problem systematically using optimization or statistical methods.  

課程目標
- Know the advanced techniques of operations research
- Create theoretical model to solve the problem in real setting
- System development and implementation 
課程要求
Prerequisites
- Operations Research: ”Operations Research” in the IM department or equivalent.
- Statistics: ”Statistics I” and “Statistics II” in the IM department or equivalent. 
預期每週課前或/與課後學習時數
 
Office Hours
另約時間 備註: TBD 
指定閱讀
待補 
參考書目
Birge, J. R., & Louveaux, F. (2011). Introduction to stochastic programming (2nd ed.). New York: Springer Verlag.
Morse, P. M. and G. E. Kimball (1951, 2012). Methods of Operations Research. Dover Publications.
Puterman, M. L. (2005). Markov Decision Processes: Discrete Stochastic Dynamic Programming. 2nd edition, Wiley-InterScience. 
評量方式
(僅供參考)
 
  1. 本校尚無訂定 A+ 比例上限。
  2. 本校採用等第制評定成績,學生成績評量辦法中的百分制分數區間與單科成績對照表僅供參考,授課教師可依等第定義調整分數區間。詳見學習評量專區 (連結)。
 
針對學生困難提供學生調整方式
 
上課形式
以錄音輔助, 以錄影輔助
作業繳交方式
團體報告取代個人報告
考試形式
書面(口頭)報告取代考試
其他
課程進度
週次
日期
單元主題
Week 1
9/02  SP: Stochastic Programming with Two-stage Recourse Problem (隨機規劃)  
Week 2
9/09  SP: The Value of Information and the Stochastic Solution (資訊價值)  
Week 3
9/16  SP: Approximation and Sampling Methods (漸進與抽樣隨機規劃)  
Week 4
9/23  Capacity Planning and Stochastic Scheduling Optimization (產能規畫與隨機排程)  
Week 5
9/30  Dynamic Supply Chain Optimization and Nonlinear Cost Modelling (動態供應鏈與非線性成本)  
Week 6
10/07  Bin-packing Problem (Three-dimensional Knapsack Problem) and Piece-wise Linearization (貨櫃裝載三維度背包問題與分段線性化)  
Week 7
10/14  Multi-Objective Decision Analysis (多準則決策分析)  
Week 8
10/21  Literature Review Project 
Week 9
10/28  Specialist Lecture (專家演講與教學: 作業研究與實證)  
Week 10
11/04  Portfolio Optimization, Vendor Selection and Order Allocation (投資組合、廠商評選與訂單配置最佳化)  
Week 11
11/11  DEA: Data Envelopment Analysis (數據包絡分析法)  
Week 12
11/18  DEA: Data Envelopment Analysis (數據包絡分析法)  
Week 13
11/25  Stochastic Dynamic Programming (隨機動態規劃)  
Week 14
12/02  MDP: Markov Decision Processes (馬可夫決策過程)  
Week 15
12/09  RL: Reinforcement Learning (強化學習)  
Week 16
12/16  Team Project Discussion (分組實作討論)  
Week 17
12/23  No Class  
Week 18
12/30  No Class