Pythagorean Fuzzy Choquet Integral Based MABAC Method for Multiple Attribute Group Decision Making

By Xindong Peng, Yong Yang. International Journal of Intelligent Systems, 2016

311 citations recorded by the source corpus.

In this paper, we define the Choquet integral operator for Pythagorean fuzzy aggregation operators, such as Pythagorean fuzzy Choquet integral average (PFCIA) operator and Pythagorean fuzzy Choquet integral geometric (PFCIG) operator. The operators not only consider the importance of the elements or their ordered positions but also can reflect the correlations among the elements or their ordered positions. It is worth pointing out that most of the existing Pythagorean fuzzy aggregation operators are special cases of our operators. Meanwhile, some basic properties are discussed in detail. Later, we propose two approaches to multiple attribute group decision making with attributes involving dependent and independent by the PFCIA operator and multi‐attributive border approximation area comparison (MABAC) in Pythagorean fuzzy environment. Finally, two illustrative examples have also been taken in the present study to verify the developed approaches and to demonstrate their practicality and effectiveness.

Subfields: Control and Systems Engineering, Management, Monitoring, Policy and Law, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/33147d25128f5d8131278e517b9a2b2974a38137

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Citations in the corpus

Modification of the Best-Worst and MABAC methods: A novel approach based on interval-valued fuzzy-rough numbers (2018, methodology): “Arithmetic averaging is most commonly used for the aggregation of the expert decisions (Zhai et al., 2010; Peng and Yang, 2016).”
Pythagorean fuzzy set: state of the art and future directions (2017, methodology): “Consequently, Peng and Yang (2016b) provided more flexible and richer expression called Pythagorean fuzzy linguistic set (PFLS), which can include the range of intuitionistic fuzzy linguistic set.”
Pythagorean Fuzzy Information Measures and Their Applications (2017, methodology): “Peng and Yang 16 discussed their relationship and proposed a superiority and inferiority ranking multiple attribute group decision making (MAGDM) method.”
Assessing occupational risks in pipeline construction using FMEA-based AHP-MOORA integrated approach under Pythagorean fuzzy environment (2019, methodology): “Since Pythagorean fuzzy sets first emerged, several studies have been performed on multicriteria decision-making (MCDM) problem using Pythagorean fuzzy set (Zeng et al. 2016; Zhang and Xu 2014; Yang et al. 2016; Liang and Xu 2017; Zhang 2016; Peng and Yang 2016; Ren et al. 2016).”
A HYBRID FUZZY AHP-MABAC MODEL: APPLICATION IN THE SERBIAN ARMY – THE SELECTION OF THE LOCATION FOR DEEP WADING AS A TECHNIQUE OF CROSSING THE RIVER BY TANKS (2018, unknown): “Peng and Yang (2016) developed Pythagorean Fuzzy Choquet Integral Based MABAC Method.”