<?xml version="1.0" encoding="UTF-8"?>
<doi_batch version="5.3.1" xmlns="http://www.crossref.org/schema/5.3.1" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:jats="http://www.ncbi.nlm.nih.gov/JATS1" xmlns:ai="http://www.crossref.org/AccessIndicators.xsd" xsi:schemaLocation="http://www.crossref.org/schema/5.3.1 http://www.crossref.org/schema/deposit/crossref5.3.1.xsd">
 <head>
  <doi_batch_id>aspg-31-1840-1791686800</doi_batch_id>
  <timestamp>20261011024640</timestamp>
  <depositor>
   <depositor_name>American Scientific Publishing Group</depositor_name>
   <email_address>admin@americaspg.com</email_address>
  </depositor>
  <registrant>American Scientific Publishing Group</registrant>
 </head>
 <body>
  <journal>
   <journal_metadata language="en">
    <full_title>International Journal of Advances in Applied Computational Intelligence</full_title>
    <abbrev_title>IJAACI</abbrev_title>
    <issn media_type="electronic">2833-5600</issn>
   </journal_metadata>
   <journal_issue>
    <publication_date media_type="online">
     <year>2022</year>
    </publication_date>
    <journal_volume>
     <volume>2</volume>
    </journal_volume>
    <issue>1</issue>
   </journal_issue>
   <journal_article publication_type="full_text">
    <titles>
     <title>Interval Valued Neutrosophic VIKOR Method for Assessment Green Suppliers in Supply Chain</title>
    </titles>
    <contributors>
     <person_name sequence="first" contributor_role="author">
      <given_name>Shereen</given_name>
      <surname>Zaki</surname>
      <affiliations>
       <institution>
        <institution_name>Faculty of computers and Informatics, Zagazig University, Zagazig, 44519, Egypt</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Mahmoud M.</given_name>
      <surname>Ibrahim</surname>
      <affiliations>
       <institution>
        <institution_name>Faculty of computers and Informatics, Zagazig University, Zagazig, 44519, Egypt</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Mahmoud M.</given_name>
      <surname>Ismail</surname>
      <affiliations>
       <institution>
        <institution_name>Faculty of computers and Informatics, Zagazig University, Zagazig, 44519, Egypt</institution_name>
       </institution>
      </affiliations>
     </person_name>
    </contributors>
    <jats:abstract>
     <jats:p>In order to remain competitive, businesses must now invest in developing environmentally responsible green suppliers. The purpose of this article is to determine which vendors should be incorporated into green supplier growth programs in order to enhance their ecological sustainability, as well as the suppliers' current green/environmental efficiency. Factor evaluation was used to examine the reliability of the parameters used to assess green suppliers' efficiency and overall quality. To determine which provider offers the greatest ecological performance, the suggested technique uses a hybrid interval-valued neutrosophic set (IVNS) and VIKOR structure to assign relative importance to each criterion. To manage ambiguity while choosing choices, we combine the neutrosophic method with the VIKOR technique. We used 10 criteria and ten vendors in this research to demonstrate the usefulness and effectiveness of the suggested framework. The suggested methodology is applied in the application.</jats:p>
    </jats:abstract>
    <publication_date media_type="online">
     <year>2022</year>
    </publication_date>
    <pages>
     <first_page>15</first_page>
     <last_page>22</last_page>
    </pages>
    <publisher_item>
     <item_number item_number_type="article-number">1840</item_number>
    </publisher_item>
    <ai:program name="AccessIndicators">
     <ai:license_ref applies_to="vor">https://creativecommons.org/licenses/by/4.0/</ai:license_ref>
    </ai:program>
    <doi_data>
     <doi>10.54216/IJAACI.020102</doi>
     <resource>https://www.americaspg.com/journal/31/article/1840</resource>
     <collection property="text-mining">
      <item>
       <resource mime_type="application/pdf">https://www.americaspg.com/storage/71686304971.pdf</resource>
      </item>
     </collection>
    </doi_data>
   </journal_article>
  </journal>
 </body>
</doi_batch>
