課程資訊
課程名稱
水資源系統分析
Water Resources System Analysis 
開課學期
100-2 
授課對象
工學院  水利工程組  
授課教師
游景雲 
課號
CIE7040 
課程識別碼
521 M3890 
班次
 
學分
全/半年
半年 
必/選修
選修 
上課時間
星期二6,7,8(13:20~16:20) 
上課地點
土研407 
備註
總人數上限:34人 
Ceiba 課程網頁
http://ceiba.ntu.edu.tw/1002WRS 
課程簡介影片
 
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課程概述

This course is intended to develop a student’s ability to quantitatively and qualitatively evaluate approaches to water resource management in terms of their technical feasibility, economic merits, and public policy implications. We will discuss the fundamental optimization theories and the application potentials for water resources and environmental systems planning, resources conservation, and pollution control. The operational research techniques, including linear programming, dynamic programming, nonlinear programming, stochastic programming and multi-objective programming, will be introduced. Both engineering and economic principles will be incorporated into optimization exercises that are used as a means of policy analysis. Most examples cover typical planning, design, and operation problems for water resources and environmental infrastructure with regard to complex multidisciplinary decision-making. Water resources system models addressing the interfaces and interactions between the built environment and the natural systems will be emphasized. Students are expected to finish an term-project according to their research interest to demonstrate their understanding of the course contents.
 

課程目標
1) Introduce water resources systems modeling approach.
2) Classical theory of maxima and minima
3) Linear Programming
4) Nonlinear Programming
5) Dynamic Programming
6) Optimization software
7) Policy instruments and regulation
8) Decision making theory & uncertainty
9) Stochastic programming
10) Discussion of water resource management and planning
 
課程要求
Assignments 40%
Mid-term Exam 25%
Term Project 35%
Participation 5%
 
預期每週課後學習時數
 
Office Hours
 
指定閱讀
 
參考書目
1. Loucks DP, van Beek E, Water resources systems planning and management: an
introduction to methods, models and applications. UNESCO, 2005 , Paris.
Available online: http://ecommons.library.cornell.edu/handle/1813/2804
2. Luenberger D., Linear and Nonlinear Programming, Addison-Wesley.
3. Miranda, Mario J. and Paul Fackler, Applied Computational Economics and
Finance, MIT Press: Cambridge, MA, 2002
4. Daniel P. Loucks, Jery R. Stedinger, Douglas A. Haith, Water Resources
Systems Planning and Analysis , Prentice Hall, 1981
5. S. Boyd and L. Vandenberghe, Convex Optimization. Cambridge,U.K.: Cambridge
Univ. Press. Available online: http://www.stanford.edu/~boyd/cvxbook/
6. Pike R. Optimization for engineering systems. New York: Van Nostrand
Reinhold, 1986. Available online: http://www.mpri.lsu.edu/bookindex.html
7. G. V. Reklaitis,A. Ravindran, and K.M. Ragsdell, Engineering optimization
methods and application. Wiley, New York, 1983
 
評量方式
(僅供參考)
   
課程進度
週次
日期
單元主題
第1週
2/21  Introduction
1. Course Introduction
2. System Concept
3. Water Resources Management and planning
 
第2週
2/28  228 Memorial Day 
第3週
3/06  Basic theory
1. Classical theory of maxima and minima
2. Example of simple optimization
Software Installation
1. Excel
2. GAMS
3. Matlab 
第4週
3/13  Basic theory: Linearity & Non-linearity
Mathematics background: Convexity and concavity
Using computer to solve optimization problem : Excel Solver
Using computer to solve optimization problem : GAMS
 
第5週
3/20  Solve optimization problem : GAMS;
 
第6週
3/27  Linear Programming
1. Introduction and basic property
2. Simplex method
3. Slackness and artificial variables
 
第7週
4/03  Linear Programming
1. Introduction and basic property
2. Simplex method
3. Slackness and artificial variables

Discussion of externality 
第8週
4/10  Linear Programming
1. Duality Theorem
2. The Dual Simplex Method
 
第9週
4/17  Non-linear Programming
1. Interior method
2. 1st order necessary condition & 2nd order condition
3. Minimization and Maximization of Convex Function
4. Basic descent methods.
Policy Tools 
第10週
4/24  Non-linear Programming
4. Basic descent methods.
5. Newton Method
6. Conjugate Direction Method
Policy Tools 
第11週
5/01  Quasi-Newton Methods
Nonlinear Programming
1. Constrained nonlinear optimization
2. 1st order necessary condition & 2nd order condition
3. Lagrange Multiplier
4. Primal Methods
5. Penalty and Barrier Methods .
 
第12週
5/08  Regulation
1. Government policy tools
2. Pigovian tax & Coase Theorem
3. Regulation & Standards
Water Right Issue
1. Riparian Doctrine
2. Prior Appropriation Doctrine
3. Public Trust Doctrine
 
第13週
5/15  Matlab optimization toolbox;
Regulation & Standards  
第14週
5/22  Dynamic optimization
1. Optimal control theory
2. Hoteling rule
3. Dynamic programming
 
第15週
5/29  Uncertainty & Decision Making