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  <doi_batch_id>aspg-21-2855-1791475935</doi_batch_id>
  <timestamp>20261008161215</timestamp>
  <depositor>
   <depositor_name>American Scientific Publishing Group</depositor_name>
   <email_address>admin@americaspg.com</email_address>
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  <journal>
   <journal_metadata language="en">
    <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>
   </journal_metadata>
   <journal_issue>
    <publication_date media_type="online">
     <year>2024</year>
    </publication_date>
    <journal_volume>
     <volume>24</volume>
    </journal_volume>
    <issue>4</issue>
   </journal_issue>
   <journal_article publication_type="full_text">
    <titles>
     <title>Enhancing Inventory Management through Advanced Technologies and Mathematical Methods: Utilizing Neutrosophic Fuzzy Logic</title>
    </titles>
    <contributors>
     <person_name sequence="first" contributor_role="author">
      <given_name>C. Balakrishna</given_name>
      <surname>Moorthy</surname>
      <affiliations>
       <institution>
        <institution_name>Engineering Department, University of Technology and Applied Sciences, 211 Salalah, Oman.</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>D.</given_name>
      <surname>Rajani</surname>
      <affiliations>
       <institution>
        <institution_name>Department of Mathematics, V R Siddhartha Engineering College, Siddhartha Academy of Higher Education (Deemed to be University), Vijayawada - 520007, Andhra Pradesh, India.</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>A. P.</given_name>
      <surname>Pushpalatha</surname>
      <affiliations>
       <institution>
        <institution_name>Department of Mathematics, Velammal College of Engineering and Technology, Madurai- 625009, Tamil Nadu, India</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>S.</given_name>
      <surname>Ramya</surname>
      <affiliations>
       <institution>
        <institution_name>PG Department of Mathematics, Bhaktavatsalam Memorial College for Women, Chennai – 600080, Tamil Nadu, India.</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>A.</given_name>
      <surname>Selvaraj</surname>
      <affiliations>
       <institution>
        <institution_name>Department of Mathematics, Vel Tech Rangarajan Dr Sagunthala R &amp; D Institute of Science and Technology, Chennai – 600062, Tamil Nadu, India.</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Mohit</given_name>
      <surname>Tiwari</surname>
      <affiliations>
       <institution>
        <institution_name>Department of Computer Science and Engineering, Bharati Vidyapeeth’s College of Engineering, Delhi -110063, India.</institution_name>
       </institution>
      </affiliations>
     </person_name>
    </contributors>
    <jats:abstract>
     <jats:p>Optimal inventory management is one of the most critical components for companies to thrive in the competitive market while meeting their customers’ demands, reducing costs, and developing their operations. In this paper, the utilization of different technologies and instruments ranging from the most modern ones to mathematical ones was analyzed to demonstrate how the system can function successfully. It is expected that Neutrosophic fuzzy logic is one of the most complicated approaches that allow for proper uncertainty management, forecasting, and inventory control improvements. Fundamentally, the process could be that much more insightful due to the availability of mathematical modelling and on-the-go support systems. Through the use of dynamic programming with the help of Python tools to process these models, Full optimization under fuzzy demand is possible to achieve. Therefore, one could conclude that companies have many opportunities to develop their operations, reduce costs, and keep their customers happy even in a highly dynamic and uncertain business environment.</jats:p>
    </jats:abstract>
    <publication_date media_type="online">
     <year>2024</year>
    </publication_date>
    <pages>
     <first_page>50</first_page>
     <last_page>58</last_page>
    </pages>
    <publisher_item>
     <item_number item_number_type="article-number">2855</item_number>
    </publisher_item>
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     <ai:license_ref applies_to="vor">https://creativecommons.org/licenses/by/4.0/</ai:license_ref>
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    <doi_data>
     <doi>10.54216/IJNS.240403</doi>
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