Purpose -Green supply chain management (GSCM) has become an important issue with increasing awareness of environmental protection. A firm's environmental approach is not only relevant to its inner efforts, but its suppliers' environmental performance is also important. The aim of this study is to propose an integrated multi-criteria decision-making (MCDM) approach based on intuitionistic fuzzy set (IFS) and grey relational analysis (GRA) for green supplier selection. Design/methodology/approach -Green supplier selection is a MCDM process that contains different kinds of uncertainties. Because of the vagueness and imprecision of decision makers' evaluations and subjectivity of the criteria, IFS and GRA are exploited to handle these uncertainties. Findings -A numerical example is presented for the proposed approach. The analyses of the results show that fuzzy set theory and grey theory can be used jointly for green supplier selection problems in uncertain environments. Originality/value -There are different kinds of uncertainties in the supplier selection process. The novelty of this study is to use proper uncertainty methods in different steps instead of denoting the whole selection process by the same uncertainty theory. Supplier selection problems occupy wide space in operations research literature. Different criteria are used in different papers. In this study, detailed literature review has been carried out and some criteria among frequently confronted ones proposed for green supplier selection.
Purpose
– In the literature, many multi attributes decision making (MADM) models allow evaluation of the alternatives considering their current or last performance. However, in some MADM problems, not only current performance of alternatives but also their past performance should be taken into account in order to select the most appropriate alternative. For this reason, the purpose of this paper is to develop four procedures to evaluate the alternatives in MADM problems with multi terms.
Design/methodology/approach
– This study uses dynamic operators to aggregate the evaluation in different terms and then, grey relational analysis (GRA) and technique for order preference by similarity to ideal solution (TOPSIS) methods are utilized to determine the most appropriate alternative. Thus, four procedures which consist of these operators and methods are developed to evaluate the alternatives in multi terms.
Findings
– Some numerical examples are presented for the proposed procedures in multi-terms. Moreover, these four procedures are compared with other four procedures. The analyses of the results show that dynamic aggregation operators based on intuitionistic fuzzy set (IFS) and interval valued intuitionistic fuzzy sets (IVIFS) with GRA and TOPSIS can be used jointly for MADM problems in which alternatives are evaluated for different terms.
Originality/value
– One of the significant mistakes faced in some MADM problems is to take into account the current performance of alternatives or is to ignore their past performance. The right selection depends on past and current performance of the alternatives. The novelty of this study is to propose four procedures for solving MADM problems in multi terms based on IFS and IVIFS using dynamic aggregation operators and GRA and TOPSIS methods.
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