<?xml version="1.0" encoding="UTF-8"?>
<ArticleSet>
  <Article>
    <Journal>
      <PublisherName></PublisherName>
      <JournalTitle>علم تصمیم گیری و سیستم های هوشمند</JournalTitle>
      <Issn>3060-7574</Issn>
      <Volume>2</Volume>
      <Issue>مجموعه مقالات انگلیسی</Issue>
      <PubDate PubStatus="epublish">
        <Year>1404</Year>
        <Month>12</Month>
        <Day>01</Day>
      </PubDate>
    </Journal>
    <ArticleTitle>Target Setting in Production Technologies with Multiple Component Processes</ArticleTitle>
    <VernacularTitle>Target Setting in Production Technologies with Multiple Component Processes</VernacularTitle>
    <FirstPage>1</FirstPage>
    <LastPage>20</LastPage>
    <Language>EN</Language>
    <AuthorList>
      <Author>
        <FirstName>Nasim</FirstName>
        <LastName>Nasrabadi</LastName>
        <Affiliation>Department of Mathematics, Faculty of Mathematical Science and Statistics, University of Birjand, Birjand, Iran</Affiliation>
      </Author>
    </AuthorList>
    <PublicationType>Journal Article</PublicationType>
    <History>
      <PubDate PubStatus="received">
        <Year>1404</Year>
        <Month>10</Month>
        <Day>02</Day>
      </PubDate>
    </History>
    <Abstract>&lt;p&gt;In this paper, we consider non-parametric production technologies with multiple component production processes, where each component uses both specific and shared inputs to produce specific and shared outputs. Investigating the issue of target setting within these technologies, we show that how efficient benchmarks for in-efficient units within the multi-component production technologies can be obtained by using basic envelopment and multiplier Data Envelopment Analysis models. Furthermore, we formulate efficient frontier of multi-component technology and develop a mixed integer optimization model that obtains closest targets for each in-efficient activity. The proposed models are finally illustrated on a real data set consisting 102 public universities in the UK.  &lt;/p&gt;</Abstract>
    <OtherAbstract Language="FA">&lt;p&gt;In this paper, we consider non-parametric production technologies with multiple component production processes, where each component uses both specific and shared inputs to produce specific and shared outputs. Investigating the issue of target setting within these technologies, we show that how efficient benchmarks for in-efficient units within the multi-component production technologies can be obtained by using basic envelopment and multiplier Data Envelopment Analysis models. Furthermore, we formulate efficient frontier of multi-component technology and develop a mixed integer optimization model that obtains closest targets for each in-efficient activity. The proposed models are finally illustrated on a real data set consisting 102 public universities in the UK.  &lt;/p&gt;</OtherAbstract>
    <ObjectList>
      <Object Type="keyword">
        <Param Name="value">Pareto-efficient</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">convexity</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">projection point</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">closest target</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">پارتو بهینه</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">تحدب</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">نقطه تصویر</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">نزدیک ترین الگو</Param>
      </Object>
    </ObjectList>
    <ArchiveCopySource DocType="pdf">https://dsisj.com/index.php/dsisj/article/download/77/39</ArchiveCopySource>
  </Article>
</ArticleSet>
