2021 Transportation Network Analysis

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Academic unit or major
Graduate major in Civil Engineering
Asakura Yasuo 
Course component(s)
Lecture    (ZOOM)
Day/Period(Room No.)
Tue3-4()  Fri3-4()  
Course number
Academic year
Offered quarter
Syllabus updated
Lecture notes updated
Language used
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Course description and aims

Based on the nonlinear optimization theories and algorithms, User Equilibrium (UE) in a transport network is formulated and solved. A variety of UE models are presented including deterministic UE with fixed demand, deterministic UE with variable demand and stochastic UE.
Through understanding the variety of UE model formulations and solution algorithms, this course aims to provide knowledge on how the UE models are applied to travel demand forecasting and transport network planning and management.

Student learning outcomes

By the end of the course, students will be able to:
1) understand the roles of transport network user equilibrium,
2) understand non-linear optimization theories and algorithms,
3) understand a variety of network UE models and algorithms,
4) understand how those models are applied to transport planning and management.


transport network, user equilibrium, non-linear programming

Competencies that will be developed

Specialist skills Intercultural skills Communication skills Critical thinking skills Practical and/or problem-solving skills

Class flow

The instructor will mainly give lectures and related exercises.

Course schedule/Required learning

  Course schedule Required learning
Class 1 roles of transport network analysis understand roles of transport network analysis
Class 2 graph representation of transport network understand graph representation
Class 3 link cost function understand link cost function
Class 4 nonlinear optimization without constraints understand nonlinear programming
Class 5 nonlinear optimization with constraints understand nonlinear programming
Class 6 formulation of user equilibrium with fixed demand formulating of user equilibrium with fixed demand
Class 7 solution algorithm for nonlinear optimization solving algorithm for nonlinear optimization
Class 8 solution algorithm for user equilibrium with fixed demand solution algorithm for user equilibrium with fixed demand
Class 9 intermediate summary and exercise exercises for fundamental methodologies
Class 10 formulation of user equilibrium with variable demand formulating user equilibrium with variable demand
Class 11 solution for user equilibrium with variable demand solving user equilibrium with variable demand
Class 12 formulation of stochastic user equilibrium formulating stochastic user equilibrium
Class 13 solution for stochastic user equilibrium solving stochastic user equilibrium
Class 14 application to travel demand forecasting application to travel demand forecasting

Out-of-Class Study Time (Preparation and Review)

To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to textbooks and other course material.


Sheffi, Y. (1985) Urban Transportation Networks: Equilibrium Analysis with Mathematical Programming Methods, Prentice Hall.

Reference books, course materials, etc.


Assessment criteria and methods

exercise and report (40%), exams(60%)

Related courses

  • CVE.D301 : Traffic and Transportation Systems

Prerequisites (i.e., required knowledge, skills, courses, etc.)


Contact information (e-mail and phone)    Notice : Please replace from "[at]" to "@"(half-width character).


Office hours

appointment by e-mail is necessary

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