Multi-attributive border approximation area comparison (MABAC) method based on normal q-rung orthopair fuzzy environment

Abstract

The normal intuitionistic fuzzy number (NIFN), which membership function and non-membership function are expressed by normal fuzzy numbers (NFNs), can better describe the normal distribution phenomenon in the real world, but it cannot deal with the situation where the sum of membership function and non-membership function is greater than 1. In order to make up for this defect, based on the idea of q-rung orthopair fuzzy numbers (q-ROFNs), we put forward the concept of normal q-rung orthopair fuzzy numbers (q-RONFNs), and its remarkable characteristic is that the sum of the qth power of membership function and the qth power of non-membership function is less than or equal to 1, so it can increase the width of expressing uncertain information for decision makers (DMs). In this paper, firstly, we give the basic definition and operational laws of q-RONFNs, propose two related operators to aggregate evaluation information from DMs, and develop an extended indifference threshold-based attribute ratio analysis (ITARA) method to calculate attribute weights. Then considering the multi-attributive border approximation area comparison (MABAC) method has strong stability, we combine MABAC with q-RONFNs, put forward the q-RONFNs-MABAC method, and give the concrete decision steps. Finally, we apply the q-RONFNs-MABAC method to solve two examples, and prove the effectiveness and practicability of our proposed method through comparative analysis.

Waste Clothing Recycling Channel Selection Using a CoCoSo-D Method Based on Sine Trigonometric Interaction Operational Laws with Pythagorean Fuzzy Information

“…The ITARA is a new approach for assigning semiobjective weight to attributes proposed by Hatefi [52]. This method extracts almost similar attribute values from the performance data of existing alternatives based on decentralized logic and assigns small weights to attributes [53,54]. The ITARA method has been widely used in recent years.…”

“…The ITARA method has been widely used in recent years. Liu et al [53] extended the ITARA method in q-RONFNs (normal q-rung orthopair fuzzy numbers) environment to obtain attribute weight. Chang et al [54] added the concept of aspiration level to the ITARA method for attribute weight of sustainable supplier evaluation in the electronic manufacturing industry.…”

“…In 2019, Hatefi [53] proposed an ITARA approach based on the concepts of indifference threshold and discrete logic. The attribute semi-objective weights are computed by this approach in MADM problems, which can be obtained from decision matrix data rather than inviting experts to provide information about attributes.…”

A multiattribute group decision-making method based on a new aggregation operator and the means and variances of interval-valued intuitionistic fuzzy values

“…Furthermore, Atanassov 5 defined the concept of intuitionistic fuzzy sets (IFSs), which are a strong tool used to address hesitation and uncertainty. IFSs have been widely applied in multiattribute decision-making (MADM) [6][7][8][9]11,[13][14][15] . To overcome the shortcomings of IFSs, Atanassov and Gargov 16 proposed the concept of interval-valued intuitionistic fuzzy sets (IVIFSs).…”

Decision Support in Selecting a Reliable Strategy for Sustainable Urban Transport Based on Laplacian Energy of T-Spherical Fuzzy Graphs

“…New approaches are also gaining popularity in recent years, such as the Characteristic Object's Method (COMET) [37,38], Stable Preference Ordering Towards Ideal Solution (SPOTIS) [39,40], Sequential Interactive Modelling for Urban Systems (SIMUS) [41], the Full Consistency Method (FUCOM) [42], the Best-Worst Method (BWM) [43], Combined Compromise Solution (COCOSO) [44], Additive Ratio Assessment (ARAS) [45], Multi-Attributive Border Approximation Area Comparison (MABAC) [46] or Potentially All Pairwise Rankings of all Possible Alternatives (PAPRIKA) [47]. These approaches extend classical assumptions about the distance from ideal solutions, compromise evaluation, linear programming or pairwise comparison.…”