A fuzzy multi attribute decision framework with integration of QFD and grey relational analysis. (January 2019)

• Record Type: Journal Article
• Authors: Yazdani, Morteza; Kahraman, Cengiz; Zarate, Pascale; Onar, Sezi Cevik
• Is Part Of: Expert systems with applications. Volume 115(2019)
• Page Start: 474
• Page End: 485
• Publication Date: 2019-01
• Subjects: Fuzzy decision making -- Grey relational analysis -- Interval valued fuzzy -- Multi attribute decision making -- Quality function deployment; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2018.08.017
• Languages: English
• ISSNs: 0957-4174

Abstract

Highlights: Supply chain performance indicators evaluation is Multi-Criteria Decision-Making problem. Criteria values are determined in interval valued fuzzy linguistic. An integrated version of QFD and grey relational analysis. The investigation carried out under a European Commission project. Abstract: Objective: This paper proposes a multi attribute decision support model in a supply chain in order to solve complex decision problems. The paper provides a platform to ease decision process through the integration of quality function deployment (QFD) and grey relational analysis (GRA) in demonstrating main supply chain drivers under fuzzy environment. Methodology: The proposed method is important because of several points: First of all, in a supply chain system, evaluation factors are not really independent and must be addressed in relation to the external factors such as customer requirements. Hence, we have applied QFD tool. Second, due to the constant uncertainty in the supply chain environment, fuzziness among the factors has to be considered. So, an interval valued fuzzy model was implemented. Third, to examine the proposed decision system in reality, it was applied inR isk andU ncertainC onditions forA gricultureP roductionS ystems (RUC-APS) project. Contribution: An integrated version of QFD and GRA is presented. It is assumed that QFD can act to measure optimal solutions based on the distance to ideal solutions. In an interval-valued fuzzy environment the enormous volume of computation by Euclidean distance doesn't allow decision makers to obtain the results easily. This drawback is addressed using gray relational analysis. The gray relational coefficient is integrated to the fuzzy QFD to measure the distance of potential solutions from ideal solutions. This integration facilitates decision making process in further problems once big data are available. Results: To obtain the importance degrees of logistic indicators in the supply chain, expert team considered the environmental, social & cultural, and economic factors as external dimension of the QFD. The other dimension of QFD includes supply chain drivers such as quality, environmental management system, supply chain flexibility, corporate social responsibility, transportation service condition, and financial stability. The decision model is solved and the ranking of indicators is achieved. A sensitivity analysis helps to test and check the performance of the decision model.