Abstract
Decision-making environment often encounters complexity along its processes, especially in the context of multidisciplinary scientific research. This can commonly be seen in engineering, computing, finance, astrology and other different areas. It is of great restriction in dealing with the practical problems which have diverse demands and properties. There is a growing body of literature that recognizes the importance of dealing with the complexity in decision making environment. The reliability and the transparency are the dominant feature of the integration of fuzzy network and Z-numbers. However, much of the research up to now has been descriptive in nature of the features. Hence, this proposed method is unique and novel because it offers some interesting insight of dealing with reliability and transparency of information in Z-hesitant fuzzy network decision-making environment. The fuzzy networks have the functionality under rule bases of fuzzy systems where it is recognized by its transparency and precision. The proposed method makes use of fuzzy network with the incorporation of hesitant fuzzy sets to assimilate decision information towards alternatives. For the validation and applicability purposes of the proposed method, the case study of stock evaluation assessed by a number of decision makers has been utilized as a real-world problem. The performance of the proposed method is evaluated respectively by applying the Spearman’s rho correlation. The result shows that the proposed method performs as the established method with the consideration of additional dominant features.
Highlights
The fuzzy network approach has been introduced by Gegov [1] to infuse transparency in decision making
This is proven as the precision of single rule base and multiple rule base in the fuzzy system serves a moderate level of transparency and accuracy in countering multiplex procedures of problem solving [2]
In 2009, Vicenc Torra [4] originated the concept of Hesitant Fuzzy Set (HFS) where every possible evaluation made by decision makers are permitted as the membership degree values of HFS which is defined as: Definition 1 Hesitant fuzzy set (HFS) returns a subset of [0, 1] when fixed set, X receives HFS as a function [15]
Summary
The fuzzy network approach has been introduced by Gegov [1] to infuse transparency in decision making. Fuzzy network capable of serving the final decisions well as it carries the importance of criteria and decision makers expertise throughout the formulation In this situation, because of unequivocal and sufficient information of the inner structure of the modelling process present, the white-box interpretation further enhances the description of transparency in the model [2]. This proposed method allows decision makers to access the performance of alternatives in terms of benefit and cost criteria, increase the level of transparency in the process of decision making.
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More From: International Journal of Computational Intelligence Systems
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