A QFD-based fuzzy MCDM approach for supplier selection


DURSUN M., KARSAK E. E.

APPLIED MATHEMATICAL MODELLING, vol.37, no.8, pp.5864-5875, 2013 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 37 Issue: 8
  • Publication Date: 2013
  • Doi Number: 10.1016/j.apm.2012.11.014
  • Journal Name: APPLIED MATHEMATICAL MODELLING
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.5864-5875
  • Keywords: Supplier selection, Quality function deployment (QFD), Multi-criteria decision making, Decision support, Fuzzy weighted average, QUALITY FUNCTION DEPLOYMENT, DESIGN REQUIREMENTS, MULTIPLE-CRITERIA, MODEL, DECISION, METHODOLOGY, MANAGEMENT
  • Galatasaray University Affiliated: Yes

Abstract

Supplier selection is a highly important multi-criteria group decision making problem, which requires a trade-off between multiple criteria exhibiting vagueness and imprecision with the involvement of a group of experts. In this paper, a fuzzy multi-criteria group decision making approach that makes use of the quality function deployment (QFD) concept is developed for supplier selection process. The proposed methodology initially identifies the features that the purchased product should possess in order to satisfy the company's needs, and then it seeks to establish the relevant supplier assessment criteria. Moreover, the proposed algorithm enables to consider the impacts of inner dependence among supplier assessment criteria. The upper and the lower bounds of the weights of supplier assessment criteria and ratings of suppliers are computed by using the fuzzy weighted average (FWA) method. The FWA method allows for the fusion of imprecise and subjective information expressed as linguistic variables or fuzzy numbers. The method produces less imprecise and more realistic overall desirability levels, and thus it rectifies the problem of loss of information. A fuzzy number ranking method that is based on area measurement is used to obtain the final ranking of suppliers. The computational procedure of the proposed framework is illustrated through a supplier selection problem reported in an earlier study. (C) 2012 Elsevier Inc. All rights reserved.