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Fall 2016
CEE 6210 Transportation Systems Analysis
Preliminaries
Instructor: Dr. Sadra Sharifi sadra.sharifi@aggiemail.usu.edu
ENGR 231 Tu Th 10:30 – 11:00 am
797-7109 Or by appointment
Course Description
Introduction to systems approach to analyze and design transportation systems. Focuses on key
modeling and systems concepts of a transportation system. Modeling approaches include linear
programming, simplex method, network analysis, simulation, and decision theory.
Course Objective
The objective of this course is to teach students the fundamental conceptual elements of a
transportation system and how one begins to go about analyzing and designing particular
transportation systems. By the end of this course, students should be able to apply these basic skills
to their research problems.
Course Outcomes
 Proven themselves proficient in the fundamentals in the field of transportation.
 Demonstrate the ability to apply key modeling and systems concepts learned in this class to
model real-life transportation problems.
 Demonstrate the capability to write a technical report and communicate the results of their
solution approach to other engineering professionals.
Prerequisites
CEE 3030 (Uncertainty in Engineering Analysis) or Equivalent
Grading
 Homework Assignments 10%
 Project/Presentation 30%
 Midterms 30%
 Final Exam 30%
2
Textbook
[ASW] Anderson, D.R., Sweeney, D.J., and Williams, T.A. (2005) An Introduction to
Management Science, Quantitative Approach to Decision Making, 11th
Edition, Thomson South-
Western (required).
Reference Texts
1. [J&B] Jensen, P.A. & Bard, J.F. (2003) Operations Research Models and Methods, John
Wiley & Sons, Inc.
2. [DeE] Denardo, E.V. (2003) The Science of Decision Making: A Problem-Based
Approach Using Excel, Wiley & Sons, Inc.
3. [H&L] Hillier, F.S. & Lieberman, G.J. (1990) Introduction to Operations Research,
McGraw Hill.
4. [TaB] Taylor, B.W. (2004) Introduction to Management Science, Prentice Hall.
5. [D&T] Dantzig, G.B & Thapa, M.N. (1997) Linear Programming 1: Introduction,
Springer.
6. [D&T] Dantzig, G.B & Thapa, M.N. (2003) Linear Programming 2: Theory and
Extensions, Springer.
7. [AMO] Ahuja, R.K., Magnanti, T.L., and Orlin, J.B. (1993) Network Flows, Prentice
Hall.
8. [MGE] Monahan, G.E. (2000) Management Decision Making: Spreadsheet Modeling,
Analysis, and Applications, Cambridge University Press.
9. [B&F] Blanchard, B.S. & Fabrycky, W.J. (1998) Systems Engineering and Analysis,
3rd
Edition, Prentice Hall.
10. [WHP] Williams, H.P (2001) Model Building in Mathematical Programming, 4th
Edition, Wiley.
11. [SuJ] Sussman, J. (2000) Introduction to Transportation Systems, Artech House
Publishers.
12. [RWW] ReVelle, C.S., Whitlatch, E.E., and Wright, J.R. (2004) Civil and
Environmental Systems Engineering, 2nd
Edition, Prentice Hall.
13. [C&M] Church, R.L. & Murray, A.T. (2009) Business Site Selection, Location Analysis,
and GIS, Wiley & Sons, Inc.
14. [S&L] Sinha, K.C. & Labi, S. (2007) Transportation Decision Making: Principles of
Project Evaluation and Programming, Wiley & Sons, Inc.
3
Academic Honesty
The University expects that students and faculty alike maintain the highest standards of academic
honesty. For the benefit of students who may not be aware of specific standards of the University
concerning academic honesty, the following information is quoted from The Code of Policies
and Procedures for Students at Utah State University (revised April 2002), Article V, Section 3:
Acts of academic dishonesty include but are not limited to:
Cheating: (1) using or attempting to use or providing others with any unauthorized assistance in
taking quizzes, tests, examinations, or in any other academic exercise or activity, including
working in a group when the instructor has designated that the quiz, test, examination, or any
other academic exercise or activity be done “individually”; (2) depending on the aid of sources
beyond those authorized by the instructor in writing papers, preparing reports, solving problems,
or carrying out other assignments; (3) substituting for another student, or permitting another
student to substitute for oneself, in taking an examination or preparing academic work; (4)
acquiring tests or other academic material belonging to a faculty member, staff member, or
another student without express permission; (5) continuing to write after time has been called on
a quiz, test, examination, or any other academic exercise or activity; (6) submitting substantially
the same work for credit in more than one class, except with prior approval of the instructor; or
(7) engaging in any form of research fraud.
Falsification: altering or fabricating any information or citation in an academic exercise or
activity.
Plagiarism: representing, by paraphrase or direct quotation, the published or unpublished work
of another person as one’s own in any academic exercise or activity without full and clear
acknowledgment. It also includes using materials prepared by another person or by an agency
engaged in the sale of term papers or other academic materials.
Violations of the above policy will subject the offender to the University discipline
procedures as outlined in Article VI, Section 1 (paragraphs A, E, F, G, and H) of the Code.
See the USU Code of Policies and Procedures for details.
4
Tentative Course Outline
1. System Definitions and Concepts ([B&F] Ch. 1 to 2, [SuJ] Ch. 1 to 5, [RWW] Ch. 1,
[S&L] Ch. 1 to 4)
1.1 What is a System?
1.2 Transportation (or Civil) Infrastructure Systems
1.3 Transportation Network
1.4 Why Systems Modeling
1.5 Modeling Process of a Transportation System
2. Problem Solving and Decision Making ([ASW] Ch. 1, [SuJ] Ch. 10 to 11, [C&M] Ch. 3)
2.1 Quantitative Analysis
2.2 Mathematical Models
2.3 Examples
2.4 Modeling Techniques
3. Linear Programs ([ASW] Ch. 2 to 6, [RWW] Ch. 1 to 4)
3.1 Problem Formulation
3.2 Graphical Solution Procedure
3.3 Simplex Procedure
3.4 Sensitivity Analysis
3.5 Duality
3.6 Applications
3.7 Computer Software (e.g., Excel, MATLAB)
4. Fundamentals of Network Models ([ASW] Ch. 7 to 9, [RWW] Ch. 6, [C&M] Ch. 4 and 9)
4.1 Graphical Representation
4.2 Network Characteristics
4.3 Conservation of Flow
4.4 Algebraic Structure
4.4.1 Primal Formulation
4.4.2 Dual Formulation
4.5 Network Flow Problems
4.5.1 The Transportation Problem
4.5.2 The Transshipment Problem
4.5.3 The Minimum Cost Flow Problem
4.5.4 The Maximal Flow Problem
4.6 Integer Linear Programming
4.6.1 Types of Integer Linear Programming Models
4.6.2 Graphical and Computer Solutions
4.6.3 Applications Involving 0-1 Variables
4.6.4 Modeling Flexibility Provided by 0-1 Integer Variables
5
5. Project Scheduling: PERT/CPM ([ASW] Ch. 10, [RWW] Ch. 8)
5.1 Project Scheduling with Known Activity Times
5.2 Project Scheduling with Uncertain Activity Times
5.3 Considering Time-Cost Trade-Offs
6. Simulation ([ASW] Ch. 13)
6.1 Simulation Concepts
6.2 Random Number Generator
6.3 Simulation Applications
6.4 Traffic Simulation
7. Decision Making ([ASW] Ch. 14 and 15, [RWW] Ch. 9, [S&L] Ch. 1, 18 to 20)
7.1 Decision Making Using Deterministic Models
7.2 Decision Making Under Uncertainty
7.3 Goal Programming
7.4 Multi-criteria Decision Making

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cee6210_f16

  • 1. 1 Fall 2016 CEE 6210 Transportation Systems Analysis Preliminaries Instructor: Dr. Sadra Sharifi sadra.sharifi@aggiemail.usu.edu ENGR 231 Tu Th 10:30 – 11:00 am 797-7109 Or by appointment Course Description Introduction to systems approach to analyze and design transportation systems. Focuses on key modeling and systems concepts of a transportation system. Modeling approaches include linear programming, simplex method, network analysis, simulation, and decision theory. Course Objective The objective of this course is to teach students the fundamental conceptual elements of a transportation system and how one begins to go about analyzing and designing particular transportation systems. By the end of this course, students should be able to apply these basic skills to their research problems. Course Outcomes  Proven themselves proficient in the fundamentals in the field of transportation.  Demonstrate the ability to apply key modeling and systems concepts learned in this class to model real-life transportation problems.  Demonstrate the capability to write a technical report and communicate the results of their solution approach to other engineering professionals. Prerequisites CEE 3030 (Uncertainty in Engineering Analysis) or Equivalent Grading  Homework Assignments 10%  Project/Presentation 30%  Midterms 30%  Final Exam 30%
  • 2. 2 Textbook [ASW] Anderson, D.R., Sweeney, D.J., and Williams, T.A. (2005) An Introduction to Management Science, Quantitative Approach to Decision Making, 11th Edition, Thomson South- Western (required). Reference Texts 1. [J&B] Jensen, P.A. & Bard, J.F. (2003) Operations Research Models and Methods, John Wiley & Sons, Inc. 2. [DeE] Denardo, E.V. (2003) The Science of Decision Making: A Problem-Based Approach Using Excel, Wiley & Sons, Inc. 3. [H&L] Hillier, F.S. & Lieberman, G.J. (1990) Introduction to Operations Research, McGraw Hill. 4. [TaB] Taylor, B.W. (2004) Introduction to Management Science, Prentice Hall. 5. [D&T] Dantzig, G.B & Thapa, M.N. (1997) Linear Programming 1: Introduction, Springer. 6. [D&T] Dantzig, G.B & Thapa, M.N. (2003) Linear Programming 2: Theory and Extensions, Springer. 7. [AMO] Ahuja, R.K., Magnanti, T.L., and Orlin, J.B. (1993) Network Flows, Prentice Hall. 8. [MGE] Monahan, G.E. (2000) Management Decision Making: Spreadsheet Modeling, Analysis, and Applications, Cambridge University Press. 9. [B&F] Blanchard, B.S. & Fabrycky, W.J. (1998) Systems Engineering and Analysis, 3rd Edition, Prentice Hall. 10. [WHP] Williams, H.P (2001) Model Building in Mathematical Programming, 4th Edition, Wiley. 11. [SuJ] Sussman, J. (2000) Introduction to Transportation Systems, Artech House Publishers. 12. [RWW] ReVelle, C.S., Whitlatch, E.E., and Wright, J.R. (2004) Civil and Environmental Systems Engineering, 2nd Edition, Prentice Hall. 13. [C&M] Church, R.L. & Murray, A.T. (2009) Business Site Selection, Location Analysis, and GIS, Wiley & Sons, Inc. 14. [S&L] Sinha, K.C. & Labi, S. (2007) Transportation Decision Making: Principles of Project Evaluation and Programming, Wiley & Sons, Inc.
  • 3. 3 Academic Honesty The University expects that students and faculty alike maintain the highest standards of academic honesty. For the benefit of students who may not be aware of specific standards of the University concerning academic honesty, the following information is quoted from The Code of Policies and Procedures for Students at Utah State University (revised April 2002), Article V, Section 3: Acts of academic dishonesty include but are not limited to: Cheating: (1) using or attempting to use or providing others with any unauthorized assistance in taking quizzes, tests, examinations, or in any other academic exercise or activity, including working in a group when the instructor has designated that the quiz, test, examination, or any other academic exercise or activity be done “individually”; (2) depending on the aid of sources beyond those authorized by the instructor in writing papers, preparing reports, solving problems, or carrying out other assignments; (3) substituting for another student, or permitting another student to substitute for oneself, in taking an examination or preparing academic work; (4) acquiring tests or other academic material belonging to a faculty member, staff member, or another student without express permission; (5) continuing to write after time has been called on a quiz, test, examination, or any other academic exercise or activity; (6) submitting substantially the same work for credit in more than one class, except with prior approval of the instructor; or (7) engaging in any form of research fraud. Falsification: altering or fabricating any information or citation in an academic exercise or activity. Plagiarism: representing, by paraphrase or direct quotation, the published or unpublished work of another person as one’s own in any academic exercise or activity without full and clear acknowledgment. It also includes using materials prepared by another person or by an agency engaged in the sale of term papers or other academic materials. Violations of the above policy will subject the offender to the University discipline procedures as outlined in Article VI, Section 1 (paragraphs A, E, F, G, and H) of the Code. See the USU Code of Policies and Procedures for details.
  • 4. 4 Tentative Course Outline 1. System Definitions and Concepts ([B&F] Ch. 1 to 2, [SuJ] Ch. 1 to 5, [RWW] Ch. 1, [S&L] Ch. 1 to 4) 1.1 What is a System? 1.2 Transportation (or Civil) Infrastructure Systems 1.3 Transportation Network 1.4 Why Systems Modeling 1.5 Modeling Process of a Transportation System 2. Problem Solving and Decision Making ([ASW] Ch. 1, [SuJ] Ch. 10 to 11, [C&M] Ch. 3) 2.1 Quantitative Analysis 2.2 Mathematical Models 2.3 Examples 2.4 Modeling Techniques 3. Linear Programs ([ASW] Ch. 2 to 6, [RWW] Ch. 1 to 4) 3.1 Problem Formulation 3.2 Graphical Solution Procedure 3.3 Simplex Procedure 3.4 Sensitivity Analysis 3.5 Duality 3.6 Applications 3.7 Computer Software (e.g., Excel, MATLAB) 4. Fundamentals of Network Models ([ASW] Ch. 7 to 9, [RWW] Ch. 6, [C&M] Ch. 4 and 9) 4.1 Graphical Representation 4.2 Network Characteristics 4.3 Conservation of Flow 4.4 Algebraic Structure 4.4.1 Primal Formulation 4.4.2 Dual Formulation 4.5 Network Flow Problems 4.5.1 The Transportation Problem 4.5.2 The Transshipment Problem 4.5.3 The Minimum Cost Flow Problem 4.5.4 The Maximal Flow Problem 4.6 Integer Linear Programming 4.6.1 Types of Integer Linear Programming Models 4.6.2 Graphical and Computer Solutions 4.6.3 Applications Involving 0-1 Variables 4.6.4 Modeling Flexibility Provided by 0-1 Integer Variables
  • 5. 5 5. Project Scheduling: PERT/CPM ([ASW] Ch. 10, [RWW] Ch. 8) 5.1 Project Scheduling with Known Activity Times 5.2 Project Scheduling with Uncertain Activity Times 5.3 Considering Time-Cost Trade-Offs 6. Simulation ([ASW] Ch. 13) 6.1 Simulation Concepts 6.2 Random Number Generator 6.3 Simulation Applications 6.4 Traffic Simulation 7. Decision Making ([ASW] Ch. 14 and 15, [RWW] Ch. 9, [S&L] Ch. 1, 18 to 20) 7.1 Decision Making Using Deterministic Models 7.2 Decision Making Under Uncertainty 7.3 Goal Programming 7.4 Multi-criteria Decision Making