Novel green supplier selection method by combining quality function deployment with partitioned Bonferroni mean operator in interval type-2 fuzzy environment

Abstract Green supplier selection (GSS) plays a significant role in promoting enterprise development. Quality function deployment (QFD) ensures that green supplier assessment criteria are in accordance with the characteristics that purchased products ought to possess. The partitioned Bonferroni mean (PBM) operator assumes that all criteria are partitioned into several clusters, where criteria in the same clusters are interrelated, while criteria in different clusters are irrelevant, and it can be used to deal with GSS problems in which all criteria are partitioned into several clusters. Furthermore, interval type-2 fuzzy sets (IT2FSs) can efficiently express vagueness and imprecision, and possess powerful processing abilities. In this paper, we propose a novel GSS method by combining QFD with the PBM operator in the context of IT2FSs. Firstly, we present the interval type-2 fuzzy PBM (IT2FPBM) operator and interval type-2 fuzzy weighted PBM (IT2FWPBM) operator, and discuss several of their properties. Thereafter, we transform the preference values of the importance degrees of customer needs (CNs) into those of technical criteria (TC) through the relationships between CNs and TC, based on QFD. Moreover, the criteria are partitioned on the basis of the literature review on GSS criteria. Finally, a bike-share case is used to illustrate the applicability of the presented method, and various comparisons are used to display the superiority of the presented method.

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