Hybrid soft computing models applied to graph theory / Muhammad Akram, Fariha Zafar.

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Hybrid soft computing models applied to graph theory / Muhammad Akram, Fariha Zafar.

9783030160203 (electronic book)
3030160203 (electronic book)
9783030160197
303016019X

https://doi.org/10.1007/978-3-030-16020-3
https://doi.org/10.1007/978-3-030-16

Cham, Switzerland : Springer, [2020].

English

1 online resource (xxv, 434 pages) : illustrations.

10.1007/978-3-030-16020-3 doi
10.1007/978-3-030-16

QA166.175

511/.5

This book describes a set of hybrid fuzzy models showing how to use them to deal with incomplete and/or vague information in different kind of decision-making problems. Based on the authors research, it offers a concise introduction to important models, ranging from rough fuzzy digraphs and intuitionistic fuzzy rough models to bipolar fuzzy soft graphs and neutrosophic graphs, explaining how to construct them. For each method, applications to different multi-attribute, multi-criteria decision-making problems, are presented and discussed. The book, which addresses computer scientists, mathematicians, and social scientists, is intended as concise yet complete guide to basic tools for constructing hybrid intelligent models for dealing with some interesting real-world problems. It is also expected to stimulate readers creativity thus offering a source of inspiration for future research.

Includes bibliographical references and index.

Access limited to authorized users.

Online resource; title from PDF title page (SpringerLink, viewed April 11, 2019).

Studies in fuzziness and soft computing ; v. 380.

Print version: 9783030160197

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