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    <journal-meta>
      <journal-id journal-id-type="nlm-ta">REA Press</journal-id>
      <journal-id journal-id-type="publisher-id">Null</journal-id>
      <journal-title>REA Press</journal-title><issn pub-type="ppub">3042-0199</issn><issn pub-type="epub">3042-0199</issn><publisher>
      	<publisher-name>REA Press</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">https://doi.org/10.22105/opt.v1i1.19</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
        <subj-group><subject>Neutrosophic data envelopment anal, data envelopment analysis, Performance analysis, Efficiency analysis, Neutrosophic number.</subject></subj-group>
      </article-categories>
      <title-group>
        <article-title>Neutrosophic Data Envelopment Analysis: a Comprehensive Review and Current Trends</article-title><subtitle>Neutrosophic Data Envelopment Analysis: a Comprehensive Review and Current Trends</subtitle></title-group>
      <contrib-group><contrib contrib-type="author">
	<name name-style="western">
	<surname>Kshitish </surname>
		<given-names>Kumar Mohanta</given-names>
	</name>
	<aff>Department of Mathematics, Indira Gandhi National Tribal University, Amarkantak, 484887, Madhya Pradesh, India.</aff>
	</contrib><contrib contrib-type="author">
	<name name-style="western">
	<surname>Deena Sunil</surname>
		<given-names>Sharanappa</given-names>
	</name>
	<aff>Department of Mathematics, Indira Gandhi National Tribal University, Amarkantak, 484887, Madhya Pradesh, India.</aff>
	</contrib></contrib-group>		
      <pub-date pub-type="ppub">
        <month>01</month>
        <year>2024</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>12</day>
        <month>01</month>
        <year>2024</year>
      </pub-date>
      <volume>1</volume>
      <issue>1</issue>
      <permissions>
        <copyright-statement>© 2024 REA Press</copyright-statement>
        <copyright-year>2024</copyright-year>
        <license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/2.5/"><p>This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p></license>
      </permissions>
      <related-article related-article-type="companion" vol="2" page="e235" id="RA1" ext-link-type="pmc">
			<article-title>Neutrosophic Data Envelopment Analysis: a Comprehensive Review and Current Trends</article-title>
      </related-article>
	  <abstract abstract-type="toc">
		<p>
			The concept of a neutrosophic set is a comprehensive extension of both fuzzy sets and Intuitionistic Fuzzy Sets (IFSs). It allows decision makers to assign three distinct membership degrees, enabling a more precise representation of uncertainty. Neutrosophic Data Envelopment Analysis (Neu-DEA) is an extended version of the Data Envelopment Analysis (DEA) and Fuzzy DEA (FDEA) concepts. It aims to assess the performance of Decision Making Units (DMUs) within a neutrosophic environment. Neu-DEA specifically tackles the challenges associated with evaluating performance when the input and output data are incomplete, ambiguous, or unsure. As a result, the Neu-DEAs have attracted substantial attention from scholars and academics. This article aims to provide an academic overview of the present state, development patterns, and future research directions of the Neu-DEA research. To do this, the study examines relevant publications using two analytical approaches: description analysis and literature review.
		</p>
		</abstract>
    </article-meta>
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