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  <doi_batch_id>aspg-21-4030-1791472213</doi_batch_id>
  <timestamp>20261008151013</timestamp>
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  <journal>
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    <full_title>International Journal of Neutrosophic Science</full_title>
    <abbrev_title>IJNS</abbrev_title>
    <issn media_type="print">2692-6148</issn>
    <issn media_type="electronic">2690-6805</issn>
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     <year>2026</year>
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    <journal_volume>
     <volume>27</volume>
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    <issue>2</issue>
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   <journal_article publication_type="full_text">
    <titles>
     <title>Neutrosophic Average Edge Connectivity with Applications to Communication Networks</title>
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      <given_name>Aparna</given_name>
      <surname>Tripathy</surname>
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       <institution>
        <institution_name>Department of Mathematics, C.V. Raman Global University, Bhubaneswar, Odisha, India</institution_name>
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      <given_name>Amaresh Chandra</given_name>
      <surname>Panda</surname>
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       <institution>
        <institution_name>Department of Mathematics, C.V. Raman Global University, Bhubaneswar, Odisha, India</institution_name>
       </institution>
      </affiliations>
     </person_name>
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      <given_name>Siva Prasad</given_name>
      <surname>Behera</surname>
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       <institution>
        <institution_name>Department of Mathematics, C.V. Raman Global University, Bhubaneswar, Odisha, India</institution_name>
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      <given_name>Prasanta Kumar</given_name>
      <surname>Raut</surname>
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        <institution_name>Department of Mathematics, Trident Academy of Technology, Bhubaneswar, Odisha, India</institution_name>
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      <given_name>Mana</given_name>
      <surname>Donganont</surname>
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       <institution>
        <institution_name>Department of Mathematics, School of Science, University of Phayao, Phayao 56000, Thailand</institution_name>
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      <given_name>Said</given_name>
      <surname>Broumi</surname>
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        <institution_name>Laboratory of Information Processing, Faculty of Science Ben M’Sik, University of Hassan II, Casablanca, Morocco</institution_name>
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     <jats:p>Average edge connectivity is a fundamental concept in graph theory, widely employed to evaluate the robustness of networks through the analysis of local edge cuts. Classical fuzzy extensions allow for graded membership, yet they fail to clearly distinguish between inherent uncertainty and definite absence of edges. To overcome this limitation, we introduce the notion of neutrosophic average edge connectivity, a tri-valued connectivity measure formulated within the framework of single-valued neutrosophic graphs (SVNGs). In this study, we rigorously define neutrosophic local edge cuts, establish key theoretical results including bounds and monotonicity properties, and design efficient algorithms tailored for particular families of graphs. The applicability of the proposed framework is demonstrated through a detailed communication-network case study, which highlights its capacity to capture structural resilience under indeterminate conditions. Overall, the proposed approach generalizes classical robustness indicators and provides a comprehensive tool for analyzing connectivity in networks characterized by vagueness, indeterminacy, and incomplete information.</jats:p>
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     <year>2026</year>
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