Approaches based on 2-tuple linguistic power aggregation operators for multiple attribute group decision making under linguistic environment

Xu, Yang; Wang, Huimin

doi:10.1016/j.asoc.2011.02.027

Cited by 170 publications

(84 citation statements)

References 40 publications

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“…It provides a parameterized family of aggregation operators that include as special cases the maximum, the minimum and the average [28]. Motivated by the idea of the OWA operator, Xu and Wang [29] developed the 2-tuple linguistic power ordered weighted averaging (2TLPOWA) operator, which can take all the decision arguments and their relationships into account. Jiang and Fan [30] proposed the 2-tuple ordered weighted geometric (TOWG) operator on the basis of the 2-tuple OWA operator.…”

Section: Literature Reviewmentioning

confidence: 99%

A Method for Multi-Criteria Group Decision Making with 2-Tuple Linguistic Information Based on Cloud Model

Zhang

Gao

et al. 2017

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This paper presents a new approach to solve the multi-criteria group decision making (MCGDM) problem where criteria values take the form of 2-tuple linguistic information. Firstly, a 2-tuple hybrid ordered weighted geometric (THOWG) operator is proposed, which synthetically considers the importance of both individual and the ordered position so as to overcome the defects of existing operators. Secondly, combining the advantages of the cloud model and 2-tuple linguistic variable, a new generating cloud method is proposed to transform 2-tuple linguistic variables into clouds. Thirdly, we further define some new cloud algorithms, such as cloud possibility degree and cloud support degree which can be respectively used to compare clouds and determine the criteria weights. Furthermore, a new approach for 2-tuple linguistic group decision making is presented on the basis of the THOWG operator, the improved generating cloud method as well as the new cloud algorithms. Finally, an example of assessing the social effects of biomass power plants (BPPS) is illustrated to verify the application and feasible of the developed approach, and a comparative analysis is also conducted to validate the effectiveness of the proposed method.

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Section: Literature Reviewmentioning

confidence: 99%

A Method for Multi-Criteria Group Decision Making with 2-Tuple Linguistic Information Based on Cloud Model

Zhang

Gao

et al. 2017

Information

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“…Much work has been completed using the fuzzy linguistic approach and the 2-tuple model in many situations: distributed agents [16], genetic learning [17], industrial engineering [18], multicriteria decision-making [19], fuzzy decision tools [20], human resource management [21], and so forth.…”

Section: Computing With Words and Fuzzy Logicmentioning

confidence: 99%

Natural Language Processing and Fuzzy Tools for Business Processes in a Geolocation Context

Truck

Abchir

2017

Advances in Artificial Intelligence

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In the geolocation field where high-level programs and low-level devices coexist, it is often difficult to find a friendly user interface to configure all the parameters. The challenge addressed in this paper is to propose intuitive and simple, thus natural language interfaces to interact with low-level devices. Such interfaces contain natural language processing (NLP) and fuzzy representations of words that facilitate the elicitation of business-level objectives in our context. A complete methodology is proposed, from the lexicon construction to a dialogue software agent including a fuzzy linguistic representation, based on synonymy.

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“…In the recent years, a variety of linguistic aggregation operators have been developed. Xu 23 classified these linguistic aggregation operators into five categories: (1) the linguistic aggregation operators which are based on linear ordering, such as the linguistic max and min operators 26,27,28,29,30 , linguistic median operator 28,29,30 , linguistic weighted median opera-tor 28,29,30 ; (2) the linguistic aggregation operators which are based on the extension principle, such as linguistic OWA operator 1,2,12 , inverse-LOWA operator 3 , linguistic weighted OWA operator 13 , these operators make computations on the fuzzy numbers that support the semantics of the linguistic labels; (3) the linguistic aggregation operators which are based on symbols 4,7 , these operators make computations on the indexes of the linguistic labels; (4) the linguistic aggregation operators which are based on the 2-tuple linguistic representation model, such as 2-tuple arithmetic mean operator 5,6 , 2-tuple OWA operator 5,8,9 , 2-tuple weighted geometric averaging (TWGA) operator 22 , 2-tuple ordered weighted geometric averaging (TOWGA) operator 22 ; (5) the linguistic aggregation operators which compute with words directly, such as extended ordered weighted averaging (EOWA) operator 16 , uncertain linguistic ordered weighted operator 10,11,17 , induced uncertain linguistic OWA operator 14,18 . For the linguistic aggregation operators in (1) − (3), the results usually do not match any of the initial linguistic terms and some approximation processes must be developed to express the results in the initial expression domain, which produces the loss of information and the lack of precision.…”

Section: Introductionmentioning

confidence: 99%

Linguistic interval 2-tuple power aggregation operators and their applications

Ruan¹,

Pei²,

Gao³

2013

IJCIS

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In this paper, we present a linguistic interval 2-tuple representation model and new linguistic interval 2-tuple aggregation operators, i.e., linguistic interval 2-tuple power average (LI2TPA) operator, linguistic interval 2-tuple weighted power average (LI2TWPA) operator and linguistic interval 2-tuple power ordered weighted average (LI2TPOWA) operator. Some desired properties of the developed operators are also studied. Moreover, we use these aggregation operators to deal with multiple attribute group decision making problems under linguistic interval 2-tuple environment. In the situations where the weighting vector of the decision makers is known, we use the LI2TWPA operator to make multiple attribute group decision. In the situations where the weighting vector of the decision makers is unknown, we use the LI2TPOWA operator to deal with multiple attribute group decision making. A numerical example is provided to show the effectiveness of our method.Keywords: Multiple attribute group decision making; Linguistic interval 2-tuple; Linguistic interval 2-tuple power average (LI2TPA) operator; Linguistic interval 2-tuple weighted power average (LI2TWPA) operator; Linguistic interval 2-tuple power ordered weighted average (LI2TPOWA) operator

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Approaches based on 2-tuple linguistic power aggregation operators for multiple attribute group decision making under linguistic environment

Cited by 170 publications

References 40 publications

A Method for Multi-Criteria Group Decision Making with 2-Tuple Linguistic Information Based on Cloud Model

A Method for Multi-Criteria Group Decision Making with 2-Tuple Linguistic Information Based on Cloud Model

Natural Language Processing and Fuzzy Tools for Business Processes in a Geolocation Context

Linguistic interval 2-tuple power aggregation operators and their applications

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