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مطالب درسي سيستمهاي منابع آب دانشگاه MIT

نوشته : موسوی در تاریخ : 88/06/04 در موضوع : كتابها-

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1.731

Water Resource Systems
Spring 2003 Syllabus

Instructor:

Prof. Dennis McLaughlin

Rm. 48-209

253-7176

dennism@mit.edu

This subject is concerned with quantitative methods for analyzing large-scale water resource problems. Topics covered include the design and management of facilities such as irrigation areas, water treatment plants, and networks of reservoirs and associated canals. Simulation models and optimization methods are often used to support analyses of water resource problems. In this subject we will be constructing simulation models with the MATLAB programming language and solving numerical optimization problems with the GAMS optimzation package. It is desirable for students taking this subject to have some background in hydrology, linear algebra and programming, although these are not strict prerequisites.

Class periods will generally be divided into 40 minutes of lecture and 40 minutes of related hands-on computer work using laptops available in the classroom.

There will be two in-class exams. Homework will vary in complexity from straightforward problem sets to mini-projects which resemble real-world applications. The grade will be based on exams (60%) and homework (40%). A detailed schedule is provided below.

Introduction, Modeling, and Simulation

No.	Date	Topic and links for examples	PS	PS links
1	Feb. 4	Case Study: Irrigation and Salination irrigation.m	PS1 out	PS1&Solutions Word PDF
2	Feb. 6	Modeling in MATLAB irrigation.m
3	Feb. 11	Probability Review I Random variables, probability distributions cstr.m inconc.dat ; runoff.m precip.dat
4	Feb. 13	Probability Review II Expectation; moments, derived distributions, Monte Carlo simulation derived_dist1.m ; derived_dist2.m	PS1 in, PS2 out	PS2&Solutions Word PDF
5	Feb. 20	Time series, computing empirical event probabilities runoff_monte.m

Optimization Concepts

No.	Date	Topic and links for examples	PS	PS links
6	Feb. 25	Formulation of Optimization Problems I Introduction to GAMS transprt.gms	PS2 in, PS3 out	PS3&Solutions Word PDF
7	Feb. 27	Formulation of Optimization Problems II convexity.m
8	Mar. 4	Optimality conditions I Example applying optimality conditions optimality.gms
9	Mar. 6	Optimality conditions II Continuation of example yield.gms
10	Mar. 11	Quantifying optimization objectives; Present value and amortization, Multiobjective optimization, parametric analysis pareto.gms	PS3 in PS4 out	PS4&Solutions Word PDF
11	Mar. 13	Introduction to stochastic optimization; Incorporating uncertainty pareto.gms
12	Mar. 18	Expected utility and risk aversion, Utility and multiobjective optimization Review for Quiz 1	PS4 in
13	Mar. 20	Quiz 1

Optimization Algorithms and Applications

No.	Date	Topic and links for examples	PS	PS links
14	April 1	Linear programming concepts and terminology GAMS examples	PS5 out	PS5&Solutions Word PDF
15	April 3	Solving linear programming problems GAMS examples
16	April 8	Shadow prices and sensitivity analysis GAMS examples	PS5 in PS6 out	PS6&Solutions Word PDF
17	April 10	Case Study: River Basin Planning
18	April 15	Nonlinear programming GAMS examples
19	April 17	Incorporating simulation models into optimization algorithms MATLAB implementation	PS6 in PS7 out	PS7&Solutions Word PDF
20	April 24	Case Study: Optimal management of irrigated agriculture
21	TBA	Dynamic programming I MATLAB implementation
22	May 1	Dynamic programming II MATLAB implementation	PS7 in, PS8 out	PS8&Solutions Word PDF
23	May 6	Case Study: Capacity expansion
24	May 8	Stochastic dynamic programming
25	May 13	Case Study: Evaluating infrastructure options in Thailand	PS8 in
26	May 15	Quiz 2