SYLLABUS
The course syllabus provided a sequential list of topics.
The course schedule should be used to determine the specific dates that particular topics will be covered.

CATALOG DESCRIPTION
Analytical approaches and algorithms to the formulation and solution of the equilibrium assignment problem for transportation networks. Emphasis on user equilibrium (UE), comparison with system optimal (SO), math programming formulations, supply functions, estimating origin-destination matrices, network design problems, destination choice.

COURSE OVERVIEW
The course comprises three, interrelated topics: (1) general network algorithms, (2) the static transportation network assignment problem, and (3) enhancements of the network assignment problem including such topics as stochastic loading and variable demand. The first topic is fundamental and positions the development of network assignment models as a component of transportation systems analysis. CEE228a is a pre-requisite for CEE228b Urban Transportation Networks II, which presents advanced topics such as path-based algorithms and dynamic traffic assignment.

REQUIREMENTS

1. Pre-requisites
   The material in CEE220a Travel Demand Analysis I and CEE221a Transportation Systems Analysis I (or the equivalents) should be considered pre-requisite for this course. Students should have a fundamental knowledge of mathematical programming. Please review related material and also obtain a good reference text in the areas of math programming, systems analysis, and general networks.
   
   
2. Texts
   1. Course Notes: Make a printed version of lecture slides from web site
   2. Sheffi,Y.(1985) Urban Transportation Networks, Prentice Hall
      [ download text (23Mb pdf), copyright (html), errata (html) ]
   3. Please also find, buy, or borrow a good mathematical programming textbook for reference.
      The web site includes a reference list (consider as-needed)
   
   
3. Projects:
   There are two required course projects. Project reports must follow format and style guidelines.
   
   
4. Grading:
   Course deliverables (with weighting scheme and due dates) include:
   
   
   1. Project 1 (10%) [Tentative Due Date: tbd]
      A project involving application of general transportation network algorithms.
   2. Midterm (30%) [Tentative Date: tbd]
      Midterm covers the material relating to basic network algorithms.
   3. Project 2 (20%) [Presentations: Week 10] Team projects and presentations during Week 10 focused on advanced algorithms for transportation network assignment associated with travel demand forecasting.
   4. Final Exam (40%) [ Monday December 9th, 4-6 pm ]
      The final exam is comprehensive, but focused on material from the last half of the course.
   
   
5. Academic Integrity
   As a UCI student, you have agreed to UCI Standards of Academic Honesty. You have selected a field which places professional integrity first and foremost. No form of academic dishonesty will be tolerated; there will be no second chances.
   
   
6. Web Site
   http://www.its.uci.edu/~mmcnally/cee/cee228a/

SOFTWARE
Spreadsheets such as Excel (with Solver) can be used for many exercises.

1. Free Trial Copies of LINDO/LINGO
2. CPLEX (linear programming package)
3. TransCAD can be accessed virtually from both ITS and ECT123.