Approaches to Multiple-Attribute Decision-Making Based on Pythagorean 2-Tuple Linguistic Bonferroni Mean Operators

Tang, Xiyue; Huang, Yan

doi:10.3390/a11010005

Cited by 8 publications

(6 citation statements)

References 85 publications

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“…These existing operators are as follows. Liu and Chen [27] discovered the theory of intuitionistic 2-tuple linguistic aggregation operators, Wei et al [28] explored the Pythagorean 2-tuple linguistic aggregation operators, Tang et al [32] presented the Pythagorean 2-tuple linguistic Bonferroni mean operators, and Ju et al [29] pioneered the q-rung orthopair 2-tuple linguistic Maclaurin symmetric mean operators. The comparative analysis by using the information of Table 1 is shown in Table 4.…”

Section: B Comparative Analysismentioning

confidence: 99%

“…The BM operator became to be a compelling strategy to assess impeccably the interrelationship among the qualities. The BM operator had resuscitated broad consideration from specialists and different researchers that was also effectively used in various fields [31][32][33]. On the other hand, global warming and climate change had heavily affected environment and human life on the earth.…”

Section: Introductionmentioning

confidence: 99%

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Weighted Bonferroni Aggregation Operators on Complex q-Rung Orthopair 2-Tuple Linguistic Variables With Application to Green Supply Chain Management

Ali,

Mahmood,

Yang

2023

IEEE Access

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In this paper, we give advanced study in complex q-rung orthopair 2-tuple linguistic variables (CQRO2-TLVs). The major theme of the paper is to evaluate the novel concept of CQRO2-TLVs and their dominant operational laws so that it can be a competent procedure to assess ambiguous and erratic information in realistic decision problems. Furthermore, we derive the weighted Bonferroni aggregation operators with weighted Bonferroni mean (WBM) and weighted geometric Bonferroni mean (WGBM) based on the CQRO2-TLV information for exploring the complex q-rung orthopair 2-tuple linguistic WBM (CQRO2-TLWBM) and complex q-rung orthopair 2-tuple linguistic WGBM (CQRO2-TLWGBM) operators. Some flexible and reliable properties and theories for the CQRO2-TLWBM and CQRO2-TLWGBM operators are investigated. We then introduce two new techniques to manage the multi-attribute decision making (MADM) issues under the fuzzy environment based on these operators. We know that a green supply chain management integrates environmental, ethical, and social concerns that make more about environmental and social responsibility correlated with design, production and distribution. In this paper, we apply the proposed techniques to green supply chain management to express the efficacy and usefulness of the proposed techniques. We finally make the comparisons of the proposed operators with some existing operators that demonstrate the effectiveness of our proposed method.INDEX TERMS Fuzzy sets, Complex q-rung orthopair (CQRO) fuzzy sets, 2-tuple linguistic variables (2-TLVs), CQRO 2-TLVs, Weighted Bonferroni aggregation operators, Weighted Bonferroni mean (WBM), Green supply chain.

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Section: B Comparative Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Weighted Bonferroni Aggregation Operators on Complex q-Rung Orthopair 2-Tuple Linguistic Variables With Application to Green Supply Chain Management

Ali,

Mahmood,

Yang

2023

IEEE Access

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“…Liu and Li [28] proposed the normal neutrosophic GBM operator and the normal neutrosophic weighted GBM operator, and also investigate their properties and special cases. In addition, the GBM operator has also been introduced into other fuzzy environments to fuse various fuzzy information [29][30][31][32], such as Pythagorean fuzzy sets, interval-valued intuitionistic fuzzy sets, Pythagorean 2-tuple linguistic sets, and linguistic neutrosophic sets.…”

Section: Aggregation Experts'preferencesmentioning

confidence: 99%

Failure Mode and Effects Analysis Considering Consensus and Preferences Interdependence

Zhu

Wang

2018

Algorithms

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Failure mode and effects analysis is an effective and powerful risk evaluation technique in the field of risk management, and it has been extensively used in various industries for identifying and decreasing known and potential failure modes in systems, processes, products, and services. Traditionally, a risk priority number is applied to capture the ranking order of failure modes in failure mode and effects analysis. However, this method has several drawbacks and deficiencies, which need to be improved for enhancing its application capability. For instance, this method ignores the consensus-reaching process and the correlations among the experts' preferences. Therefore, the aim of this study was to present a new risk priority method to determine the risk priority of failure modes under an interval-valued Pythagorean fuzzy environment, which combines the extended Geometric Bonferroni mean operator, a consensus-reaching process, and an improved Multi-Attributive Border Approximation area Comparison approach. Finally, a case study concerning product development is described to demonstrate the feasibility and effectiveness of the proposed method. The results show that the risk priority of failure modes obtained by the proposed method is more reasonable in practical application compared with other failure mode and effects analysis methods.Algorithms 2018, 11, 34 2 of 24 of limitations. Numerous alternative methods have been presented in the literature to handle some of these drawbacks [2], which could explain why focusing on these shortcomings can improve the performance of traditional FMEA. However, many practical application cases have suggested that the ranking results determined by these alternative methods are not reliable and suffer from drawbacks in some situations. The main reasons are the assumption that the experts' preferences are independent and the team of experts have reached a consensus before aggregating the experts' preferences. Therefore, it is worth studying the problem of how to determine effectively the risk priority of failure modes without considering these two assumptions.It is very important for an FMEA team to adopt a suitable aggregation method to aggregate the experts' preferences into a collective evaluation matrix before determining the failure modes ranking. Many aggregation methods that assume that experts' preferences are independent have been applied to aggregate the experts' preferences. In practice, the FMEA team experts come from different departments or industries, and their subjective preferences, which are often influenced by social, power, knowledge, and other factors, usually indicate some interdependent characteristics. On the one hand, the geometric Bonferroni mean (GBM) initially proposed by Xia et al. [9] is an efficient operator to deal with the aggregation of interdependent arguments. The GBM operator has a prominent characteristic that can easily capture the interrelationships among input arguments [9]. Therefore, it is significant to integrate the experts' preferences...

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“…Wei [8] developed the gray relational analysis (GRA) for interval-valued intuitionistic fuzzy MADM with incompletely known attribute weight information. Xu and Chen [9] defined the Bonferroni mean for aggregating the IVIFNs based on the Bonferroni mean [10][11][12][13][14][15][16][17]. Chen [18] proposed the LINMAP (Linear Programming Technique for Multidimensional Analysis of Preference) model for MADM with IVIFNs.…”

Section: Introductionmentioning

confidence: 99%

Some Interval-Valued Intuitionistic Fuzzy Dombi Hamy Mean Operators and Their Application for Evaluating the Elderly Tourism Service Quality in Tourism Destination

Wei

Gao

et al. 2018

Mathematics

Self Cite

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In this paper, we expand the Hamy mean (HM) operator and Dombi operations with interval-valued intuitionistic fuzzy numbers (IVIFNs) to propose the interval-valued intuitionistic fuzzy Dombi Hamy mean (IVIFDHM) operator, interval-valued intuitionistic fuzzy weighted Dombi Hamy mean (IVIFWDHM) operator, interval-valued intuitionistic fuzzy dual Dombi Hamy mean (IVIFDDHM) operator, and interval-valued intuitionistic fuzzy weighted dual Dombi Hamy mean (IVIFWDDHM) operator. Then the MADM models are designed with IVIFWDHM and IVIFWDDHM operators. Finally, we gave an example for evaluating the elderly tourism service quality in tourism destination to show the proposed models.

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Approaches to Multiple-Attribute Decision-Making Based on Pythagorean 2-Tuple Linguistic Bonferroni Mean Operators

Cited by 8 publications

References 85 publications

Weighted Bonferroni Aggregation Operators on Complex q-Rung Orthopair 2-Tuple Linguistic Variables With Application to Green Supply Chain Management

Weighted Bonferroni Aggregation Operators on Complex q-Rung Orthopair 2-Tuple Linguistic Variables With Application to Green Supply Chain Management

Failure Mode and Effects Analysis Considering Consensus and Preferences Interdependence

Some Interval-Valued Intuitionistic Fuzzy Dombi Hamy Mean Operators and Their Application for Evaluating the Elderly Tourism Service Quality in Tourism Destination

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