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To date, type-2 fuzzy sets have attracted much more interest of the researchers, which are more capable to handle uncertain and imprecision information than type-1 fuzzy sets. Heronian mean is a classical mean aggregation operator which can effectively consider the interrelationships between various arguments. In this paper, we extend Heronian mean to trapezoidal interval type-2 fuzzy environment and present some aggregation operators, such as trapezoidal interval type-2 fuzzy generalized Heronian mean (TIT2FGHM) operator and trapezoidal interval type-2 fuzzy weighted generalized Heronian mean (TIT2FWGHM) operator. Then, we further discuss several desirable properties and particular cases when the parameters take diverse values in detail. Moreover, concerning multiple attribute group decision making problems in which the decision attributes are interdependent and the attribute values take the forms of interval type-2 fuzzy numbers, we propose a new approach based on TIT2FWGHM operator. Finally, we provide a numerical example of providers selection to illustrate the practicality and effectiveness of the proposed method and give a comparison analysis between the proposed method and existing methods. [ABSTRACT FROM AUTHOR]

Maclaurin symmetric mean (MSM) operator is a powerful tool to integrate multiple input arguments, which has the characteristic of considering the interrelationships among the input arguments. In this paper, we extend the traditional MSM operator to the single-valued neutrosophic interval 2-tuple linguistic environment, propose some novel aggregation operators, and develop a novel method to solve multiple attribute group decision making (MAGDM) problems. Firstly, we put forward the concept of single-valued neutrosophic interval 2-tuple linguistic sets (SVN-ITLSs) by combining the definitions of single-valued neutrosophic sets and interval 2-tuple. Secondly, the Maclaurin symmetric mean is extended to the single-valued neutrosophic interval 2-tuple linguistic environment and three new aggregation operators are proposed, such as the single-valued neutrosophic interval 2-tuple linguistic Maclaurin symmetric mean (SVN-ITLMSM) operator, the single-valued neutrosophic interval 2-tuple linguistic weighted average (SVN-ITLWA) operator and the single-valued neutrosophic interval 2-tuple linguistic weighted Maclaurin symmetric mean (SVN-ITLWMSM) operator. Some desirable properties of the proposed SVN-ITLMSM operator are investigated. Thirdly, an approach to solve MAGDM problem is developed based on the proposed operators. Finally, a numerical example is given to illustrate the application and the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Dual hesitant fuzzy set (DHFS), which permits the possible membership degrees and non-membership degrees of an element having sets of values in [0,1], is considered as a powerful tool to express uncertain information in the process of multiple attribute group decision making (MAGDM). In this paper, we study the MAGDM problems in which the attribute values take the form of dual hesitant fuzzy elements and the weights of attributes and decision makers take the form of real numbers. Firstly, the normalized Hamming distance of the dual hesitant fuzzy elements is defined. Then, a new method for dealing MAGDM problems under dual hesitant fuzzy environment is proposed on the basis of grey relational analysis (GRA) theory. For the incompletely known and completely unknown information of attribute weight, some optimization models are established to determine the weights of attributes. Finally, a numerical example of investment alternative selection is given to illustrate the application of the proposed method and to demonstrate its practicality and effectiveness. [ABSTRACT FROM AUTHOR]

With respect to multiple attribute decision making (MADM) problems in which the attributes are inter-dependent and take the form of dual hesitant fuzzy elements, a new MADM method with dual hesitant fuzzy information is investigated in this paper. Firstly, by using the Choquet integral, some new aggregation operators are developed for aggregating the dual hesitant fuzzy information, such as the dual hesitant fuzzy Choquet ordered average (DHFCOA) operator, the dual hesitant fuzzy Choquet ordered geometric (DHFCOG) operator, the generalized dual hesitant fuzzy Choquet ordered average (GDHFCOA) operator and the generalized dual hesitant fuzzy Choquet ordered geometric (GDHFCOG) operator. Then, some special cases, desirable properties of these operators and the relationships between them are discussed. Furthermore, based on the DHFCOA operator, an approach to MADM is proposed under dual hesitant fuzzy environment. Finally, a numerical example is given to illustrate the application of the proposed method and to demonstrate its practicality and effectiveness. [ABSTRACT FROM AUTHOR]

In this paper, we extend the Hamacher operations to aggregate the dual hesitant fuzzy elements (DHFEs). Firstly, operational rules of DHFEs based on Hamacher t-norm and t-conorm are proposed. Then, we develop some dual hesitant fuzzy Hamacher aggregation operators based on the operational rules of DHFEs, such as dual hesitant fuzzy Hamacher weighted averaging (DHFHWA) operator, dual hesitant fuzzy Hamacher weighted geometric (DHFHWG) operator, dual hesitant fuzzy Hamacher ordered weighted averaging (DHFHOWA) operator, dual hesitant fuzzy Hamacher ordered weighted geometric (DHFHOWG) operator, dual hesitant fuzzy Hamacher hybrid averaging (DHFHHA) operator and dual hesitant fuzzy Hamacher hybrid geometric (DHFHHG) operator are proposed. Some desirable properties of these operators such as idempotency and boundedness are discussed, and some special cases of these operators are analyzed. Furthermore, a method to multiple attribute decision making (MADM) based on the proposed operators is developed. Finally, a practical example is given to illustrate the developed method and a comparison analysis is also conducted, which further demonstrates the practicality and effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper studies the multi-attribute decision making (MADM) problems under two situations that the attributes are independent and correlative, respectively, in which the attribute values take the form of dual hesitant fuzzy linguistic elements and the weights of attributes take the form of real numbers. Firstly, the concept, operational laws, score function and accuracy function of dual hesitant fuzzy linguistic element (DHFLE) are defined. For the situation that the attributes are independent, some dual hesitant fuzzy linguistic geometric aggregation operators are proposed. Considering that there exists prioritization among the attributes, we propose several dual hesitant fuzzy linguistic prioritized aggregation operators based on the prioritized average (PA) operator. Moreover, some desirable properties and special cases of these operators are investigated in detail. Based on the proposed operators, two novel approaches to MADM with dual hesitant fuzzy linguistic information are proposed. Finally, a numerical example for investment alternative selection is given to illustrate the application of the proposed methods. [ABSTRACT FROM AUTHOR]

This paper investigates multiple attribute decision making (MADM) problems in which the attribute values take the form of interval-valued dual hesitant fuzzy elements (IVDHFEs). Firstly, motivated by the concepts of dual hesitant fuzzy set (DHFS) and interval number, the concept, operational laws and comparison laws of interval-valued dual hesitant fuzzy elements are proposed. Then, based on the operational laws of IVDHFEs, some aggregation operators are developed for aggregating the interval-valued dual hesitant fuzzy information, such as the interval-valued dual hesitant fuzzy weighted aggregation operators, the interval-valued dual hesitant fuzzy ordered weighted aggregation operators, the generalized interval-valued dual hesitant fuzzy weighted aggregation operators, the generalized interval-valued dual hesitant fuzzy ordered weighted aggregation operators and the interval-valued dual hesitant fuzzy hybrid aggregation operators. Furthermore, some desirable properties of these operators and the relationships between them are discussed in detail. Based on the interval-valued dual hesitant fuzzy weighted average (IVDHFWA) operator, an approach to multiple attribute decision making is proposed under interval-valued dual hesitant fuzzy environment. Finally, a numerical example is given to illustrate the application of the proposed method and to demonstrate its practicality and effectiveness. [ABSTRACT FROM AUTHOR]

This paper investigates the multiple attribute decision making (MADM) problems in which the attribute values take the form of hesitant intuitionistic fuzzy linguistic elements (HIFLEs). Firstly, motivated by the idea of hesitant fuzzy linguistic elements and intuitionistic fuzzy numbers, the concept, operational laws and comparison laws of HIFLEs are defined. Then, some aggregation operators are developed for aggregating the hesitant intuitionistic fuzzy linguistic information, such as hesitant intuitionistic fuzzy linguistic weighted aggregation operators, hesitant intuitionistic fuzzy linguistic ordered weighted aggregation operators and hesitant intuitionistic fuzzy linguistic hybrid aggregation operators. Some desirable properties of these operators and the relationships between them are discussed. Furthermore, the hesitant intuitionistic fuzzy linguistic set is extended to hesitant intuitionistic fuzzy uncertain linguistic set, and some hesitant intuitionistic fuzzy uncertain linguistic aggregation operators are developed. Based on the hesitant intuitionistic fuzzy linguistic weighted average (HIFLWA) operator, an approach to MADM is proposed under hesitant intuitionistic fuzzy linguistic environment. Finally, a practical example is given to illustrate the application of the proposed method and to demonstrate its practicality and effectiveness. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the multiple attribute decision making (MADM) problems in which the attribute values take the form of trapezoid fuzzy 2-tuples. Firstly, we develop some trapezoid fuzzy 2-tuple linguistic aggregation operators based on the operational laws of trapezoid fuzzy 2-tuples, such as the trapezoid fuzzy 2-tuple weighted geometric (TFTWG) operator, the trapezoid fuzzy 2-tuple ordered weighted geometric (TFTOWG) operator, the generalized trapezoid fuzzy 2-tuple weighted average (GTFTWA) operator and the generalized trapezoid fuzzy 2-tuple ordered weighted average (GTFTOWA) operator. Then, we study some desirable properties of the developed operators, such as idempotency, monotonicity, commutativity and boundedness, and analyze some special cases of these operators. Furthermore, we propose an approach to multiple attribute decision making under trapezoid fuzzy linguistic environment based on the GTFTWA and TFTWG operators. Finally, an illustrative example is given to verify the proposed approach and to demonstrate its practicality and effectiveness. [ABSTRACT FROM AUTHOR]

We investigate the multi-attribute group decision making (MAGDM) problems in which the attribute values provided by the decision makers take the form of intuitionistic trapezoid fuzzy linguistic (ITrFL) information considering the uncertainty and inaccuracy of input arguments. Some new power aggregation operators called intuitionistic trapezoid fuzzy linguistic power average (ITrFLPA) operator, intuitionistic trapezoid fuzzy linguistic power weighted average (ITrFLPWA) operator, intuitionistic trapezoid fuzzy linguistic power ordered weighted average (ITrFLPOWA) operator, intuitionistic trapezoid fuzzy linguistic power hybrid weighted average (ITrFLPHWA) operator, intuitionistic trapezoid fuzzy linguistic power geometric (ITrFLPG) operator, intuitionistic trapezoid fuzzy linguistic power weighted geometric (ITrFLPWG) operator, intuitionistic trapezoid fuzzy linguistic power ordered weighted geometric (ITrFLPOWG) operator and intuitionistic trapezoid fuzzy linguistic power hybrid weighted geometric (ITrFLPHWG) operator are proposed. Then, we study some desirable properties of the proposed operators, such as idempotency, commutativity and boundedness. In addition, two novel approaches based on the proposed operators are developed to solve MAGDM problems with intuitionistic trapezoid fuzzy linguistic information. Finally, a numerical example is provided to verify the feasibility of the proposed approaches. [ABSTRACT FROM AUTHOR]