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International Conference on Recent Developments in Science, Engineering and Technology

REDSET 2017: Data Science and Analytics pp 533–540Cite as

Intuitionistic Fuzzy Shortest Path in a Multigraph

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 799))

Abstract

Mutigraphs are a generalized model of graphs. Multigraphs may have multiple edges between a pair of its vertices. The existing algorithms to find the fuzzy shortest path or intuitionistic fuzzy shortest paths in graphs is not applicable to multigraphs. Our work here is on the theory of multigraphs. In this paper we develop a method to search for an intuitionistic fuzzy shortest path in a directed multigraph and then develop, as a special case, a fuzzy shortest path in a multigraph. We re-construct classical Dijkstra’s rule that is applicable to graphs with crisp weights which can then be extendable to IFN multigraphs. It’s claimed that the tactic might play a significant role in several application areas of technology, specifically in those networks that may not be shaped into graphs but however into multigraphs.

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Author information

Authors and Affiliations

  1. Jamia Hamdard, New Delhi, India

    Siddhartha Sankar Biswas & M. N. Doja

  2. Jamia Millia Islamia, New Delhi, India

    Bashir Alam & M. N. Doja

Authors
  1. Siddhartha Sankar Biswas
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  2. Bashir Alam
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  3. M. N. Doja
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Correspondence to Siddhartha Sankar Biswas .

Editor information

Editors and Affiliations

  1. University of Arkansas, Fayetteville, AR, USA

    Brajendra Panda

  2. GD Goenka University, Gurugram, Haryana, India

    Sudeep Sharma

  3. GD Goenka University, Gurugram, Haryana, India

    Nihar Ranjan Roy

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Biswas, S.S., Alam, B., Doja, M.N. (2018). Intuitionistic Fuzzy Shortest Path in a Multigraph. In: Panda, B., Sharma, S., Roy, N. (eds) Data Science and Analytics. REDSET 2017. Communications in Computer and Information Science, vol 799. Springer, Singapore. https://doi.org/10.1007/978-981-10-8527-7_44

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  • DOI: https://doi.org/10.1007/978-981-10-8527-7_44

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-8526-0

  • Online ISBN: 978-981-10-8527-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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