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This book is a concise, yet carefully written, introduction to modern graph theory, covering ail its major recent developments. It can be used both as a reliable textbook for an introductory course and as a graduate text: on each topic it covers ail the basic material in full detail, and adds one or two deeper results (again with detailed proofs) to illustrate the more advanced methods of that field. This second edition extends the first in two ways. It offers a thoroughly revised and updated chapter on graph minors, which now includes full new proofs of two of the central Robertson-Seymour theorems (as well as a detailed sketch of the entire proof of their celebrated Graph Minor Theorem). Second, there is now a section of hints for ail the exercises, to enhance their value for both individual study and classroom use.


10,74 MB
Reinhard Diestel

graph-theory · PyPI

Graph theory has abundant examples of NP-complete problems. Intuitively, a problem isin P1 if thereisan efficient (practical) algorithm tofind a solutiontoit.On the other hand, a problem is in NP 2, if it is first efficient to guess a solution and then efficient to check that this solution is correct. It is conjectured (and not known) that P 6= NP. This is one of the great problems in ...

Data Modelling With Graph Theory — Part 1 — Introduction

Graph Theory is the study of graphs which are mathematical structures used to model pairwise relations between objects. These graphs are made up of nodes (also called points and vertices) which usually represent an object or a person, and edges (also called lines or links) which represent the relationship between the nodes. Graphs have many uses in machine learning, so this blog post will take ...


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