“…The use of grey theory to measure direct influences among patterns for the DEMATEL has been addressed in recent studies, such as [30][31][32][33][34][35][36]. These studies derived the total influence matrix by representing a direct influence as a grey number [27].…”
Section: Studies Related To Measuring Total Influencementioning
Tolerance-rough-set-based classifiers (TRSCs) are known to operate effectively on real-valued attributes for classification problems. This involves creating a tolerance relation that is defined by a distance function to estimate proximity between any pair of patterns. To improve the classification performance of the TRSC, distance may not be an appropriate means of estimating similarity. As certain relations hold among the patterns, it is interesting to consider similarity from the perspective of these relations. Thus, this study uses grey relational analysis to identify direct influences by generating a total influence matrix to verify the interdependence among patterns. In particular, to maintain the balance between a direct and a total influence matrix, an aggregated influence matrix is proposed to form the basis for the proposed grey-total-influence-based tolerance rough set (GTI-TRS) for pattern classification. A real-valued genetic algorithm is designed to generate the grey tolerance class of a pattern to yield high classification accuracy. The results of experiments showed that the classification accuracy obtained by the proposed method was comparable to those obtained by other rough-set-based methods.
“…The use of grey theory to measure direct influences among patterns for the DEMATEL has been addressed in recent studies, such as [30][31][32][33][34][35][36]. These studies derived the total influence matrix by representing a direct influence as a grey number [27].…”
Section: Studies Related To Measuring Total Influencementioning
Tolerance-rough-set-based classifiers (TRSCs) are known to operate effectively on real-valued attributes for classification problems. This involves creating a tolerance relation that is defined by a distance function to estimate proximity between any pair of patterns. To improve the classification performance of the TRSC, distance may not be an appropriate means of estimating similarity. As certain relations hold among the patterns, it is interesting to consider similarity from the perspective of these relations. Thus, this study uses grey relational analysis to identify direct influences by generating a total influence matrix to verify the interdependence among patterns. In particular, to maintain the balance between a direct and a total influence matrix, an aggregated influence matrix is proposed to form the basis for the proposed grey-total-influence-based tolerance rough set (GTI-TRS) for pattern classification. A real-valued genetic algorithm is designed to generate the grey tolerance class of a pattern to yield high classification accuracy. The results of experiments showed that the classification accuracy obtained by the proposed method was comparable to those obtained by other rough-set-based methods.
“…They evaluated supply chains based on emissions. Improving sustainability of supply chain management was addressed by Su et al [24] in situations with incomplete information. They proposed a hierarchical grey-DEMATEL approach.…”
This paper focuses on assessing sustainability of supply chains. In this paper, at first, we propose network dynamic range adjusted measure (RAM) model. Then, inverse version of network dynamic RAM model is proposed. Our inverse network dynamic data envelopment analysis (DEA) model changes both inputs and outputs of decision making units (DMUs) so that current efficiency scores of DMUs remain unchanged. We change inputs and outputs without any change in efficiency score of DMU under evaluation while inputs and outputs may have large ranges. A case study shows efficacy of our proposed model.
“…Incomplete information throughout the decision making process was considered in Su et al [8] and an integrated approach consisting of grey theory and DEMATEL was proposed to compensate incomplete information. Amindoust et al [9] and Ghadimi and Heavey [10] implemented fuzzy inference system to determine the suitable suppliers.…”
“…DEMATEL is a comprehensive method for building and analysing a structural model involving causal relationships between complex factors [8]. This aspect helps the decision maker to reveal and visualize the interdependence relationships between criteria and sub-criteria.…”
Section: Fuzzy Decision Making Trial and Evaluation Laboratory (Dematmentioning
Abstract:The term sustainability, which means maintaining a balance or acting responsibly for the future, has come into prominence in many fields. One of the most crucial practice is cooperating with convenient collaborators and composing effective supply chains in terms of social, economic and environmental considerations. Therefore, sustainable supplier selection is getting more and more important to compete in rapidly changing environment. To deal with sustainable supplier selection problem, this study aims to determine the selection of appropriate suppliers and allocation of orders to them. The proposed approach operates in three stages. In the first stage, Fuzzy Decision Making Trial and Evaluation Laboratory is used to obtain the weights of the criteria from sustainability perspective. In the second stage, by using Fuzzy Grey Relational Analysis, a set of suppliers are ranked and their suitability scores are calculated. In the last stage, optimal order quantities to be procured by the suppliers are obtained via fuzzy linear programming including imprecise data of demand, error rate and capacity.
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