Artikel

The application of fuzzy Delphi and fuzzy inference system in supplier ranking and selection

In today's highly rival market, an effective supplier selection process is vital to the success of any manufacturing system. Selecting the appropriate supplier is always a difficult task because suppliers posses varied strengths and weaknesses that necessitate careful evaluations prior to suppliers' ranking. This is a complex process with many subjective and objective factors to consider before the benefits of supplier selection are achieved. This paper identifies six extremely critical criteria and thirteen sub-criteria based on the literature. A new methodology employing those criteria and sub-criteria is proposed for the assessment and ranking of a given set of suppliers. To handle the subjectivity of the decision maker's assessment, an integration of fuzzy Delphi with fuzzy inference system has been applied and a new ranking method is proposed for supplier selection problem. This supplier selection model enables decision makers to rank the suppliers based on three classifications including ''extremely preferred'', ''moderately preferred'', and ''weakly preferred''. In addition, in each classification, suppliers are put in order from highest final score to the lowest. Finally, the methodology is verified and validated through an example of a numerical test bed.

Sprache
Englisch

Erschienen in
Journal: Journal of Industrial Engineering International ; ISSN: 2251-712X ; Volume: 10 ; Year: 2014 ; Pages: 1-16 ; Heidelberg: Springer

Klassifikation
Management
Thema
Supplier selection
Fuzzy Delphi method
Fuzzy inference system
Multiple-inputs multiple-output

Ereignis
Geistige Schöpfung
(wer)
Tahriri, Farzad
Mousavi, Maryam
Haghighi, Siamak Hozhabri
Dawal, Siti Zawiah Md
Ereignis
Veröffentlichung
(wer)
Springer
(wo)
Heidelberg
(wann)
2014

DOI
doi:10.1007/s40092-014-0066-6
Handle
Letzte Aktualisierung
10.03.2025, 11:43 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Artikel

Beteiligte

  • Tahriri, Farzad
  • Mousavi, Maryam
  • Haghighi, Siamak Hozhabri
  • Dawal, Siti Zawiah Md
  • Springer

Entstanden

  • 2014

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