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

Artikel

Purpose: 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. Design/methodology/approach: 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. Findings: 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. Originality/value: 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.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Journal: Journal of Industrial Engineering and Management (JIEM) ; ISSN: 2013-0953 ; Volume: 7 ; Year: 2014 ; Issue: 5 ; Pages: 1197-1221 ; Barcelona: OmniaScience

Klassifikation und Themen

• Klassifikation: Management
• Thema: efficient suppliers ; Grey Relational Analysis ; Data Envelopment Analysis ; ranking method ; grey numbers

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Sayyah Markabi, Mohsen ; Sabbagh, Mohammad
• Ereignis: Veröffentlichung
• (wer): OmniaScience
• (wo): Barcelona
• (wann): 2014

Weitere Informationen

• DOI: doi:10.3926/jiem.872
• Handle: http://hdl.handle.net/10419/188651
• Letzte Aktualisierung: 10.03.2025, 11:41 MEZ