1.

Record Nr.

UNINA9910741189003321

Autore

Mathew Sunil

Titolo

Weighted and Fuzzy Graph Theory / / by Sunil Mathew, John N. Mordeson, M. Binu

Pubbl/distr/stampa

Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023

ISBN

3-031-39756-8

Edizione

[1st ed. 2023.]

Descrizione fisica

1 online resource (226 pages)

Collana

Studies in Fuzziness and Soft Computing, , 1860-0808 ; ; 429

Altri autori (Persone)

MordesonJohn N

BinuM

Disciplina

006.3

Soggetti

Computational intelligence

Graph theory

Computational Intelligence

Graph Theory

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

Graphs and Weighted Graphs -- Connectivity -- More on Connectivity -- Cycle Connectivity -- Distance and Convexity -- Degree Sequences and Saturation -- Intervals and Gates -- Weighted Graphs and Fuzzy Graphs -- Fuzzy Results from Crisp Results.

Sommario/riassunto

One of the most preeminent ways of applying mathematics in real-world scenario modeling involves graph theory. A graph can be undirected or directed depending on whether the pairwise relationships among objects are symmetric or not. Nevertheless, in many real-world situations, representing a set of complex relational objects as directed or undirected is not su¢ cient. Weighted graphs o§er a framework that helps to over come certain conceptual limitations. We show using the concept of an isomorphism that weighted graphs have a natural connection to fuzzy graphs. As we show in the book, this allows results to be carried back and forth between weighted graphs and fuzzy graphs. This idea is in keeping with the important paper by Klement and Mesiar that shows that many families of fuzzy sets are lattice isomorphic to each other. We also outline the important work of Head and Weinberger that show how results from ordinary mathematics can be carried over to fuzzy mathematics. We focus on the concepts



connectivity, degree sequences and saturation, and intervals and gates in weighted graphs.