A Guide to Graph Algorithms [electronic resource] /

By:

Kloks, Ton [author.]

Contributor(s):

Material type: Text

TextPublisher: Singapore : Springer Nature Singapore : Imprint: Springer, 2022Edition: 1st ed. 2022Description: XV, 340 p. 1 illus. online resourceContent type:

text

Media type:

computer

Carrier type:

online resource

ISBN:

9789811663505

Subject(s):

Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:

005.13 23

LOC classification:

QA9.58

Online resources:

Click here to access online

Contents:

Chapter 1. Graphs -- Chapter 2. Algorithms -- Chapter 3. Problem Formulations -- Chapter 4. Recent Trends.

In: Springer Nature eBookSummary: This book A Guide to Graph Algorithms offers high-quality content in the research area of graph algorithms and explores the latest developments in graph algorithmics. The reader will gain a comprehensive understanding of how to use algorithms to explore graphs. It is a collection of texts that have proved to be trend setters and good examples of that. The book aims at providing the reader with a deep understanding of the structural properties of graphs that are useful for the design of efficient algorithms. These algorithms have applications in finite state machine modelling, social network theory, biology, and mathematics. The book contains many exercises, some up at present-day research-level. The exercises encourage the reader to discover new techniques by putting things in a clear perspective. A study of this book will provide the reader with many powerful tools to model and tackle problems in real-world scenarios.

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Chapter 1. Graphs -- Chapter 2. Algorithms -- Chapter 3. Problem Formulations -- Chapter 4. Recent Trends.

This book A Guide to Graph Algorithms offers high-quality content in the research area of graph algorithms and explores the latest developments in graph algorithmics. The reader will gain a comprehensive understanding of how to use algorithms to explore graphs. It is a collection of texts that have proved to be trend setters and good examples of that. The book aims at providing the reader with a deep understanding of the structural properties of graphs that are useful for the design of efficient algorithms. These algorithms have applications in finite state machine modelling, social network theory, biology, and mathematics. The book contains many exercises, some up at present-day research-level. The exercises encourage the reader to discover new techniques by putting things in a clear perspective. A study of this book will provide the reader with many powerful tools to model and tackle problems in real-world scenarios.

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