Algorithms for MAGDM with intuitionistic fuzzy sets and their application for evaluating the green technological innovation ability of the enterprises

2021 ◽  
Vol 40 (5) ◽  
pp. 9687-9707
Author(s):  
Jun Bao

The dual generalized Bonferroni mean (DGBM) operator is a meaningful decision-making tool which can consider the relationship between any numbers of being fused arguments and has been applied to many MAGDM domains in past few years. The intuitionistic fuzzy sets (IFSs), which is characterized by the functions of membership degree and non-membership degree, has been investigated by numerous scholars. In this manuscript, combine the DGBM operator and IFSs, the major contribution and objective of the work is to develop two new aggregation operators: the dual generalized intuitionistic fuzzy BM (DGIFBM) operator and the dual generalized intuitionistic fuzzy weighted BM (DGIFWBM) operator. The last, we give an application example for evaluating the green technological innovation ability of the enterprises and some comparative analysis to testify the effective and scientific of our developed methods.

Author(s):  
Bhagawati Prasad Joshi ◽  
Abhay Kumar

The fusion of multidimensional intuitionistic fuzzy information plays an important part in decision making processes under an intuitionistic fuzzy environment. In this chapter, it is observed that existing intuitionistic fuzzy Einstein hybrid aggregation operators do not follow the idempotency and boundedness. This leads to sometimes illogical and even absurd results to the decision maker. Hence, some new intuitionistic fuzzy Einstein hybrid aggregation operators such as the new intuitionistic fuzzy Einstein hybrid weighted averaging (IFEHWA) and the new intuitionistic fuzzy Einstein hybrid weighted geometric (IFEHWG) were developed. The new IFEHWA and IFEHWG operators can weigh the arguments as well as their ordered positions the same as the intuitionistic fuzzy Einstein hybrid aggregation operators do. Further, it is validated that the defined operators are idempotent, bounded, monotonic and commutative. Then, based on the developed approach, a multi-criteria decision-making (MCDM) procedure is given. Finally, a numerical example is conducted to demonstrate the proposed method effectively.


2014 ◽  
Vol 2014 ◽  
pp. 1-22 ◽  
Author(s):  
Juan-juan Peng ◽  
Jian-qiang Wang ◽  
Jing Wang ◽  
Xiao-hong Chen

The definition of hesitant interval-valued intuitionistic fuzzy sets (HIVIFSs) is developed based on interval-valued intuitionistic fuzzy sets (IVIFSs) and hesitant fuzzy sets (HFSs). Then, some operations on HIVIFSs are introduced in detail, and their properties are further discussed. In addition, some hesitant interval-valued intuitionistic fuzzy number aggregation operators based ont-conorms andt-norms are proposed, which can be used to aggregate decision-makers' information in multicriteria decision-making (MCDM) problems. Some valuable proposals of these operators are studied. In particular, based on algebraic and Einsteint-conorms andt-norms, some hesitant interval-valued intuitionistic fuzzy algebraic aggregation operators and Einstein aggregation operators can be obtained, respectively. Furthermore, an approach of MCDM problems based on the proposed aggregation operators is given using hesitant interval-valued intuitionistic fuzzy information. Finally, an illustrative example is provided to demonstrate the applicability and effectiveness of the developed approach, and the study is supported by a sensitivity analysis and a comparison analysis.


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