2020 Graph Theory with Engineering Application

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School of Engineering
Wimer Shmuel  Takahashi Atsushi 
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Course description and aims

Graph theory results are widely used to model and solve many engineering, social and natural science problem; it is also an excellent mean to explore proof techniques in discrete mathematics. This course aims at introducing basic graph theory concepts, and it demonstrates how they can be used in facing real-life modeling and design problem.

Student learning outcomes

The main goal of this course is to equip the students with graph theory “state of mind” in facing engineering problems. The students will acquire graph theory basic knowledge and will experiencing solutions to some common problems, which will direct them towards utilizing analytical approach in their R&D challenges, in addition to simulation and experiments, which are commonly used in R&D.


Graph theory, Algorithms, Complexity, Linear algebra, Combinatorics, and Probability

Competencies that will be developed

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

Class flow

This course aims at introducing basic graph theory concepts, and it demonstrates how they can be used in facing real-life modeling and design problem. Its approach it a mix of formal and intuition, where no previous knowledge in graph theory is assumed. There will be formal proofs of some important theorems (though few), while others will only be overviewed. Algorithms and complexity will only be briefly discussed as those are widely covered in other courses. Each of the topics will demonstrate related practical problems.

Course schedule/Required learning

  Course schedule Required learning
Class 1 Matching Maximum matching, bipartite graphs, perfect matching, matching algorithms.
Class 2 Graph coloring Vertex coloring, the chromatic number, perfect graphs, map coloring, edge coloring.
Class 3 Connectivity Vertex connectivity, edge connectivity, 3-connected graphs.
Class 4 Cliques and independent sets Shannon capacity, Turán’s theorem, Ramsey’s theorem.
Class 5 The probabilistic method Random graphs, expectation, variance, evolution of random graphs.
Class 6 Planar graphs JDuality, Euler formula, bridges, planarity recognition, the four-color problem.
Class 7 Electrical networks Circulations and tensions, the matrix-tree theorem, resistive electrical networks, perfect squares, random walks on graphs.



Reference books, course materials, etc.

All lectures slides will be available on-line.

J.A. Bondy and U.S.R. Murty, Graph Theory, Springer.
D.B. West, Introduction to Graph Theory, Prectice-Hall.

Assessment criteria and methods

Learning achievement is evaluated by the quality of the written reports, exercise problems, and etc.

Related courses

  • XEG.S405 : Topics in Digital VLSI Design
  • XEG.S605 : Advanced Topics in Digital VLSI Design

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

Students are supposed to have some background in algorithms, basic knowledge of linear algebra, combinatorics and probability.

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

atsushi [at] ict.e.titech.ac.jp

Office hours

Contact by e-mail in advance to schedule an appointment

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