A hybrid method of grey relational analysis and data envelopment analysis for evaluating and selecting efficient suppliers plus a novel ranking method for grey numbers

<p><strong>Purpose:</strong> Evaluation and selection of efficient suppliers is one of the key issues in supply chain management which depends on wide range of qualitative and quantitative criteria. The aim of this research is to develop a mathematical model for evaluating and sele...

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Bibliographic Details
Main Authors: Mohsen Sayyah Markabi, Mohammad Sabbagh
Format: Article
Language:English
Published: OmniaScience 2014-10-01
Series:Journal of Industrial Engineering and Management
Subjects:
Online Access:http://www.jiem.org/index.php/jiem/article/view/872
Description
Summary:<p><strong>Purpose:</strong> Evaluation and selection of efficient suppliers is one of the key issues in supply chain management which depends on wide range of qualitative and quantitative criteria. The aim of this research is to develop a mathematical model for evaluating and selecting efficient suppliers when faced with supply and demand uncertainties.</p><p><strong>Design/methodology/approach: </strong>In this research Grey Relational Analysis (GRA) and Data Envelopment Analysis (DEA) are used to evaluate and select efficient suppliers under uncertainties. Furthermore, a novel ranking method is introduced for the units that their efficiencies are obtained in the form of interval grey numbers.</p><p><strong>Findings:</strong> The study indicates that the proposed model in addition to providing satisfactory and acceptable results avoids time-consuming computations and consequently reduces the solution time. To name another advantage of the proposed model, we can point out that it enables us to make decision based on different levels of risk.</p><p><strong>Originality/value: </strong>The paper presents a mathematical model for evaluating and selecting efficient suppliers in a stochastic environment so that companies can use in order to make better decisions.</p>
ISSN:2013-8423
2013-0953