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  <Article>
    <Journal>
      <PublisherName>IJIRCSTJournal</PublisherName>
      <JournalTitle>International Journal of Innovative Research in Computer Science and Technology</JournalTitle>
      <PISSN>I</PISSN>
      <EISSN>S</EISSN>
      <Volume-Issue>Volume 3 Issue 4</Volume-Issue>
      <PartNumber/>
      <IssueTopic>Statistics</IssueTopic>
      <IssueLanguage>English</IssueLanguage>
      <Season>July - August 2015</Season>
      <SpecialIssue>N</SpecialIssue>
      <SupplementaryIssue>N</SupplementaryIssue>
      <IssueOA>Y</IssueOA>
      <PubDate>
        <Year>2019</Year>
        <Month>12</Month>
        <Day>02</Day>
      </PubDate>
      <ArticleType>Computer Sciences</ArticleType>
      <ArticleTitle>Fuzzy Modified TOPSIS for Supplier Selection Problem in Supply Chain Management </ArticleTitle>
      <SubTitle/>
      <ArticleLanguage>English</ArticleLanguage>
      <ArticleOA>Y</ArticleOA>
      <FirstPage>22</FirstPage>
      <LastPage>28</LastPage>
      <AuthorList>
        <Author>
          <FirstName>Dr. Raosaheb V. Latpate</FirstName>          
          <AuthorLanguage>English</AuthorLanguage>
          <Affiliation/>
          <CorrespondingAuthor>Y</CorrespondingAuthor>
          <ORCID/>
             
        </Author>
      </AuthorList>
      <DOI></DOI>
      <Abstract>Nowadays, global market is highly competitive. Major part of the capital is spent on purchasing raw material/semi finished items. The strategic decision of supply chain is to minimize the expenses on the purchase of items. There are several criteria involved in this problem; such as cost, quality, on-time delivery and long term relationship. All of these criteria are conflicting in nature and linguistic that is why technique for order preference to positive ideal solution (TOPSIS) is used. Modified TOPSIS method is invented to deal with such problems. Modified TOPSIS method is fusion of TOPSIS method and linear programming problem (LPP) method along with more variable transform &amp;Yacute;)&amp;Yacute;&amp;Scaron;&amp;Yacute;&amp;hellip;&amp;Yacute;&amp;rdquo; &amp;lowast; ). In this &amp;Yacute;&amp;rdquo;)&amp;Yacute;&amp;Scaron;&amp;Yacute;&amp;hellip;&amp;Yacute; ,method &amp;lowast; &amp;Yacute;&amp;rdquo; ,( &amp;lowast; &amp;isin; &amp;aacute;&amp;permil;&amp;sbquo;0, &amp;agrave;&amp;deg;&amp;mdash; &amp;agrave;&amp;not;&amp;para; &amp;aacute;&amp;permil;&amp;fnof; transform is used for normalization. LPP method is used to maximize the closeness coefficient for obtaining the optimal order quantity. The modified TOPSIS method not only ranks the supplier but also it gives us the idea about how much to order from the selected supplier. Thumb of rule is that more the variable transforms better the closeness coefficient. The numerical example is given to illustrate the above methods.</Abstract>
      <AbstractLanguage>English</AbstractLanguage>
      <Keywords>Supply Chain; Supplier Selection; Fuzzy; Modified TOPSIS; TOPSIS Method</Keywords>
      <URLs>
        <Abstract>https://ijircst.org/abstract.php?article_id=220</Abstract>
      </URLs>      
    </Journal>
  </Article>
</ArticleSet>