Scholarlink

<p>A non-parametric method&#xa0;based on linear programming called data envelopment analysis (DEA) assesses how well decision-making units (DMUs) perform. Traditional DEA models don’t consider internal structures or intermediate values, so they struggle to pinpoint the causes of inefficiency. One of the popular network structures that addressed this flaw by incorporating intermediate values is the two-stage network structure. Since intermediate values are crucial to network structures, a two-stage model has been developed in this study. The Neutrosophic approach has been used to address the uncertainties in real-world judgments during this process. In the end, the proposed method is used to solve a numerical example. In this example, 10 decision-making units are considered, each with 2 inputs in the first stage, an intermediate product and 2 outputs in the second stage. In the following, during successive steps, the values of total efficiency, efficiency of the first stage, and efficiency of the second stage were calculated in a Neutrosophic environment. Finally, using the Centroid Defuzzification method, the Defuzzified values of efficiency were calculated and the decision-making units were ranked.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Development of Two-stage Data Envelopment Analysis Model in Neutrosophic Environment

  • 期刊论文

  • 发表日期：

    2025年12月22日

查看全文
  • Arezoo Sadat Ayatollah,
  • Hossein Moinzad,
  • Hossein Sayyadi Tooranloo,
  • Mohammad Ali Keramati

摘要

A non-parametric method based on linear programming called data envelopment analysis (DEA) assesses how well decision-making units (DMUs) perform. Traditional DEA models don’t consider internal structures or intermediate values, so they struggle to pinpoint the causes of inefficiency. One of the popular network structures that addressed this flaw by incorporating intermediate values is the two-stage network structure. Since intermediate values are crucial to network structures, a two-stage model has been developed in this study. The Neutrosophic approach has been used to address the uncertainties in real-world judgments during this process. In the end, the proposed method is used to solve a numerical example. In this example, 10 decision-making units are considered, each with 2 inputs in the first stage, an intermediate product and 2 outputs in the second stage. In the following, during successive steps, the values of total efficiency, efficiency of the first stage, and efficiency of the second stage were calculated in a Neutrosophic environment. Finally, using the Centroid Defuzzification method, the Defuzzified values of efficiency were calculated and the decision-making units were ranked.