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Algorithms on Trees and Graphs

With Python Code

Gabriel Valiente

$214.95   $171.85

Hardback

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English
Springer Nature Switzerland AG
12 October 2021
This textbook introduces graph algorithms on an intuitive basis followed by a detailed exposition using structured pseudocode, with correctness proofs as well as worst-case analyses. Graph algorithms is a well-established subject in mathematics and computer science. Beyond classical application fields, like approximation, combinatorial optimization, graphics, and operations research, graph algorithms have recently attracted increased attention from computational biology, bioinformatics, and computational chemistry. Centered around the fundamental issue of graph isomorphism, this book goes beyond classical graph problems of shortest paths, spanning trees, flows in networks, and matchings in bipartite graphs. Advanced algorithmic results and techniques of practical relevance are presented in a coherent and consolidated way. Furthermore, Python code for all algorithms presented is given in a appendix. Numerous illustrations, examples, problems, exercises, and a comprehensive bibliography support students and professionals in using the book as a text and source of reference.
By:  
Imprint:   Springer Nature Switzerland AG
Country of Publication:   Switzerland
Edition:   2nd ed. 2021
Dimensions:   Height: 235mm,  Width: 155mm, 
Weight:   770g
ISBN:   9783030818845
ISBN 10:   3030818845
Series:   Texts in Computer Science
Pages:   387
Publication Date:  
Audience:   Professional and scholarly ,  Undergraduate
Format:   Hardback
Publisher's Status:   Active

Gabriel Valiente, PhD, is an accredited Full Professor at the Department of Computer Science and a member of the Algorithms, Bioinformatics, Complexity and Formal Methods Research Group of the Technical University of Catalonia in Barcelona, Spain. He has been lecturing on Data Structures and Algorithms at the undergraduate level and Advanced Graph Algorithms at the graduate level over the last several years. His current research is centered on combinatorial algorithms on graphs and, in particular, algorithms for comparing trees and graphs, with emphasis on algorithms in computational biology and bioinformatics.

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