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In this paper, we investigate the multi-criteria group decision-making (MCGDM) problems with incomplete weight information under T-spherical fuzzy environment. Firstly, motivated by the idea of the intuitionistic fuzzy interaction method, we propose some operation laws of T-spherical fuzzy numbers (T-SFNs), as well as some T-spherical fuzzy interaction aggregation operators, such as the T-spherical fuzzy weighted averaging interaction (T-SFWAI) operator, the T-spherical fuzzy weighted geometric interaction (T-SFWGI) operator, the T-spherical fuzzy ordered weighted interaction aggregation operators and the generalized T-spherical fuzzy interaction aggregation operators. Then, some desirable properties of the proposed T-SFWAI and T-SFWGI operators and some special cases of the generalized T-spherical fuzzy interaction aggregation operators are discussed in detail. Secondly, for the situations where the information about the weights of criteria is partly known or completely unknown, we establish two optimization models to determine the weights of criteria based on the maximizing deviation method and Lagrange function method, respectively. Thirdly, the traditional TODIM (an acronym in Portuguese of interactive and multi-criteria decision-making) approach is extended to solve MCGDM problem under the T-spherical fuzzy environment by defining the distance between T-SFNs, score function and accuracy function of T-spherical fuzzy number. Finally, a numerical example is given to illustrate the application of the extended TODIM approach, and further the sensitivity analysis and comparison analysis are carried out to demonstrate the influence of parameter on the final result and the effectiveness of the extended method. [ABSTRACT FROM AUTHOR]

By combining picture fuzzy set and 2-tuple linguistic representation model, Wei et al. (Soft Comput 22(3):989–1002, 2018) proposed the concept of picture 2-tuple linguistic set and presented some operational laws of picture 2-tuple linguistic numbers (P2TLNs). On the basis of operational laws of P2TLNs, some picture 2-tuple linguistic aggregation operators have been further developed. However, some operational laws and results derived by aggregation operators proposed by Wei et al. (Soft Comput 22(3):989–1002, 2018) are conflict with definition of picture 2-tuple linguistic number (P2TLN). In this short note, we propose some novel operational laws of P2TLNs and develop one adjusted picture 2-tuple linguistic aggregation operator, i.e., the adjusted picture 2-tuple linguistic weighted averaging operator. [ABSTRACT FROM AUTHOR]

Generalized Heronian mean (GHM) is a useful aggregation operator with the characteristic of capturing the interrelationship of evaluation information. In this paper, we propose some new operators by combining the power average operator and the GHM operator under hesitant fuzzy linguistic environment, such as the hesitant fuzzy linguistic power generalized Heronian mean (HFLPGHM) operator, the hesitant fuzzy linguistic power generalized geometric Heronian mean (HFLPGGHM) operator, the hesitant fuzzy linguistic weighted power generalized Heronian mean (HFLWPGHM) operator and the hesitant fuzzy linguistic weighted power generalized geometric Heronian mean (HFLWPGGHM) operator. Then, some special cases of the proposed HFLPGHM and HFLPGGHM operators are discussed in detail. Furthermore, based on the proposed operators, we develop a novel method to solve multi-attribute group decision-making problem under hesitant fuzzy linguistic environment. Finally, a numerical example is given to illustrate the application of the developed method and a comparison analysis is also conducted, which further demonstrates the effectiveness and feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

In the classical LINear programming technique for Multidimensional Analysis of Preference (LINMAP), the criteria are assumed to be independent, which may cause distorted results. The aim of this paper is to employ the LINMAP to develop an interval-valued intuitionistic fuzzy (IVIF) mathematical programming method for multicriteria group decision making considering not only the importance of criteria and that of their ordered positions but also the interactions among criteria and those among their ordered positions. In the spirit of LINMAP, new group consistency and group inconsistency indices based on cross-entropy and Shapley values are firstly defined by considering the interactions among criteria and among their ordered positions. To simultaneously determine the fuzzy measures on criteria set and on ordered set, a bi-objective IVIF programming model is then constructed by minimizing the inconsistency index and maximizing the consistency index. The proposed IVIF programming model is subsequently solved by transforming it into a multiobjective programming model. Furthermore, some generalizations of the proposed programming model are investigated. Finally, two examples are given to illustrate the application of the proposed method, and its superiority is demonstrated by comparing the performance of the proposed method with that of the existing methods. [ABSTRACT FROM AUTHOR]

With respect to multiple attribute group decision making (MAGDM) problems in which the attributes are dependent and the attribute values take the forms of intuitionistic linguistic numbers and intuitionistic uncertain linguistic numbers, this paper investigates two novel MAGDM methods based on Maclaurin symmetric mean (MSM) aggregation operators. First, the Maclaurin symmetric mean is extended to intuitionistic linguistic environment and two new aggregation operators are developed for aggregating the intuitionistic linguistic information, such as the intuitionistic linguistic Maclaurin symmetric mean (ILMSM) operator and the weighted intuitionistic linguistic Maclaurin symmetric mean (WILMSM) operator. Then, some desirable properties and special cases of these operators are discussed in detail. Furthermore, this paper also develops two new Maclaurin symmetric mean operators for aggregating the intuitionistic uncertain linguistic information, including the intuitionistic uncertain linguistic Maclaurin symmetric mean (IULMSM) operator and the weighted intuitionistic uncertain linguistic Maclaurin symmetric mean (WIULMSM) operator. Based on the WILMSM and WIULMSM operators, two approaches to MAGDM are proposed under intuitionistic linguistic environment and intuitionistic uncertain linguistic environment, respectively. Finally, two practical examples of investment alternative evaluation are given to illustrate the applications of the proposed methods. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the multiple attribute group decision making (MAGDM) problems with 2-tuple linguistic information. Firstly, motivated by the ideas of Choquet integral and Shapley index, we propose three 2-tuple linguistic aggregation operators called Shapley 2-tuple linguistic Choquet averaging operator, Shapley 2-tuple linguistic Choquet geometric operator and generalized Shapley 2-tuple linguistic Choquet averaging operator. Then we discuss some properties of these operators, such as idempotency, monotonicity, boundary and commutativity. Secondly, if the information about the weights of decision makers (DMs) and attributes is incompletely known, we build two models to determine the optimal fuzzy measures on DM set and attribute set, respectively. Furthermore, we develop a new method for multiple attribute group decision making under 2-tuple linguistic environment based on the proposed operators. Finally, we apply the developed MAGDM method to select the most desirable emergency alternative and the validity of the developed method is verified by comparing the evaluation results with those obtained from the existing 2-tuple correlated aggregation operators. [ABSTRACT FROM AUTHOR]

With respect to multiple attribute group decision making (MAGDM) problems in which the assessment values of attributes take the form of interval-valued hesitant uncertain linguistic elements, a novel MAGDM method is proposed in this paper. Firstly, the concept, operational laws and score function of interval-valued hesitant uncertain linguistic elements (IVHULEs) are introduced. Then, based on the operational laws of IVHULEs, some generalized aggregation operators are proposed for aggregating the interval-valued hesitant uncertain linguistic information, including the generalized interval-valued hesitant uncertain linguistic weighted aggregation operators, the generalized interval-valued hesitant uncertain linguistic ordered weighted aggregation operators and the generalized interval-valued hesitant uncertain linguistic hybrid aggregation operators. Furthermore, some desirable properties of these operators and the relationships between them are discussed. Based on the proposed operators, an approach to multiple attribute group decision making with unknown weight information is developed under interval-valued hesitant uncertain linguistic 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]

With respect to multi-attribute group decision-making (MAGDM) problems in which the attribute values take form of intuitionistic trapezoid fuzzy linguistic numbers, some new aggregation operators are proposed, such as intuitionistic trapezoid fuzzy linguistic weighted geometric operator, intuitionistic trapezoid fuzzy linguistic ordered weighted geometric operator, intuitionistic trapezoid fuzzy linguistic hybrid weighted geometric operator, intuitionistic trapezoid fuzzy linguistic generalized weighted averaging operator, intuitionistic trapezoid fuzzy linguistic generalized ordered weighted averaging operator and intuitionistic trapezoid fuzzy linguistic generalized hybrid weighted averaging operator are proposed at first. Then, some desirable properties of these proposed operators are discussed, including monotonicity, idempotency, commutativity and boundedness. Furthermore, based on the proposed operators, some novel methods are developed to solve MAGDM problems with intuitionistic trapezoid fuzzy linguistic information under different cases. Finally, an illustrative example of emergency response capability evaluation is provided to illustrate the applicability and effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

In the multi-attribute decision-making (MADM) problems, decision makers refer to the extreme attribute values in general when evaluating the alternatives. However, in the real world, the ideal solution may lie in somewhere between the extreme values. The recently proposed reference ideal method (RIM) is able to solve the problem rightly. This study aims at developing a novel MADM framework combining best–worst method (BWM), maximizing deviation method (MDM), and RIM under Z-number environment. In this framework, Z-number is used to depict the inherent uncertainty and reliability of information in the decision makers' judgments. And BWM and MDM are combined to determine the comprehensive attribute weights, in which BWM is utilized to obtain the subjective weights, while MDM is utilized to obtain the objective weights. In addition, Z-RIM is proposed by extending the traditional RIM under Z-number environment, which is employed for ranking the alternatives. An illustrative example of cloud service selection problem is implemented to illustrate the proposed framework. By comparison analysis, we demonstrate that Z-RIM can not only avoid rank reversal problem, but also generate reasonable results during the MADM processes. [ABSTRACT FROM AUTHOR]