A novel fuzzy multi-criteria decision framework for sustainable supplier selection with incomplete information


BÜYÜKÖZKAN FEYZİOĞLU G., Cifci G.

COMPUTERS IN INDUSTRY, cilt.62, sa.2, ss.164-174, 2011 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 62 Sayı: 2
  • Basım Tarihi: 2011
  • Doi Numarası: 10.1016/j.compind.2010.10.009
  • Dergi Adı: COMPUTERS IN INDUSTRY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.164-174
  • Anahtar Kelimeler: Sustainable supply chain, Supplier selection, Analytic network process, Fuzzy logic, Incomplete preference relations, ANALYTIC NETWORK PROCESS, CHAIN MANAGEMENT, PERFORMANCE EVALUATION, PROGRAMMING APPROACH, PREFERENCE RELATIONS, MULTIPLE CRITERIA, MAKING PROCEDURE, MODEL, CONSISTENCY, LOGISTICS
  • Galatasaray Üniversitesi Adresli: Evet

Özet

Both academic and corporate interest in sustainable supply chains has increased in recent years. Supplier selection process is one of the key operational tasks for sustainable supply chain management. This paper examines the problem of identifying an effective model based on sustainability principles for supplier selection operations in supply chains. Due to its multi-criteria nature, the sustainable supplier evaluation process requires an appropriate multi-criteria analysis and solution approach. The approach should also consider that decision makers might face situations such as time pressure, lack of expertise in related issue, etc., during the evaluation process. The paper develops a novel approach based on fuzzy analytic network process within multi-person decision-making schema under incomplete preference relations. The method not only makes sufficient evaluations using the provided preference information, but also maintains the consistency level of the evaluations. Finally, the paper analyzes the sustainability of a number of suppliers in a real-life problem to demonstrate the validity of the proposed evaluation model. (C) 2010 Elsevier B.V. All rights reserved.