A flexible consensus scheme for multicriteria group decision making under linguistic assessments

Parreiras, Roberta; Ekel, Petr; Martini, José Sidnei Colombo; Palhares, Reinaldo M.

doi:10.1016/j.ins.2009.11.046

Cited by 213 publications

(94 citation statements)

References 25 publications

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“…After the negotiation and investigation of the experts, they determine the 2-tuple linguistic weight vector . As the stated earlier, the expert 3 D , named as the group leader, has rich experience, knowledge and speciality in university evaluation. Obviously, his importance degree is extremely high and may be 8 s but less than 8 s , therefore, the weight of expert 3 D can be represented using the linguistic 2-tuple .…”

Section: The Magdm Methods With 2-tuple Linguistic Assessment Informationmentioning

confidence: 93%

“…Consequently, the five faculty candidates are to be evaluated using the 2-tuple linguistic information according to the linguistic term set: A A  by the latter. The worst alternative is 2 A by both methods, but the best alternative by the former is 4 A , while the best alternative by the latter is 3 A . Compared with the former, the main advantages of the latter mainly lie in the following:…”

Section: A Real Application To Evaluating University Faculty For Tenumentioning

confidence: 90%

“…For example, the experts think that the attribute 3 a is important and the weight may be 6 s but less than 6 s , thus the weight of attribute 3 a can be represented using the linguistic 2-tuple 3 3 6 ( , ) ( , 0.2) w s…”

Section: The Magdm Methods With 2-tuple Linguistic Assessment Informationmentioning

confidence: 99%

“…Multi-attribute group decision making (MAGDM) problems with linguistic information arise from a wide range of real-world situations (Jiang et al 1 ; Herrera and Herrera-Viedma 2 ; Parreiras et al 3 ). In linguistic MAGDM analysis, firstly, experts provide their assessment information from the pre-established linguistic term sets.…”

Section: Introductionmentioning

confidence: 99%

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Some Hybrid Geometric Aggregation Operators with 2-tuple Linguistic Information and Their Applications to Multi-attribute Group Decision Making

Wan¹

2013

IJCIS

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A new method is developed to solve multi-attribute group decision making (MAGDM) problem in which the attribute values, attribute weights and expert weights are all in the form of 2-tuple linguistic information. First, the operation laws for 2-tuple linguistic information are defined and the related properties of the operation laws are studied. Then, some new hybrid geometric aggregation operators with 2-tuple linguistic information are developed, involving the 2-tuple hybrid weighted geometric average (THWAG) operator, the 2-tuple hybrid linguistic weighted geometric average (T-HLWG) operator and the extended 2-tuple hybrid linguistic weighted geometric average (ET-HLWG) operator. These hybrid geometric aggregation operators generalize the existing 2-tuple linguistic geometric aggregation operators and reflect the important degrees of both the given 2-tuples and the ordered positions of the 2-tuples. In the proposed decision method, using the ET-HLWG operators the individual overall preference values of the alternatives are integrated into the collective ones of the alternatives, which are used to rank the alternatives. The method can sufficiently consider the importance degrees of different experts and thus relieve the influence of those unfair arguments on the decision results. A real example of evaluating university faculty is given to illustrate the proposed method and the comparison analysis demonstrates the universality and flexibility of the proposed method in this paper.

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Section: The Magdm Methods With 2-tuple Linguistic Assessment Informationmentioning

confidence: 93%

Section: A Real Application To Evaluating University Faculty For Tenumentioning

confidence: 90%

Section: The Magdm Methods With 2-tuple Linguistic Assessment Informationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Some Hybrid Geometric Aggregation Operators with 2-tuple Linguistic Information and Their Applications to Multi-attribute Group Decision Making

Wan¹

2013

IJCIS

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show abstract

“…This approach is categorized as one of the MCDM methods in which value judgments of criteria are expressed through crisp values. However, in real situations when analyzing and quantifying different types of variables from different spheres, it is generally found that the information is imprecise and lacks crispness due to inaccurate estimates of values from decision maker judgments (Herrera et al 2008;Parreiras et al 2010). Thus, in real situations, where the information is imprecise, the alternatives can be better assessed by means of fuzzy sets or linguistic variables (Herrera et al 2008;Ashtiani et al 2009).…”

Section: Introductionmentioning

confidence: 99%

Decision making under uncertainty using a qualitative TOPSIS method for selecting sustainable energy alternatives

Afsordegan

Sánchez

Agell

et al. 2016

Int. J. Environ. Sci. Technol.

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Multi-criteria decision-making methods support decision makers in all stages of the decision-making process by providing useful data. However, criteria are not always certain as uncertainty is a feature of the real world. MCDM methods under uncertainty and fuzzy systems are accepted as suitable techniques in conflicting problems that cannot be represented by numerical values, in particular in energy analysis and planning. In this paper, a modified TOPSIS method for multi-criteria group decision-making with qualitative linguistic labels is proposed. This method addresses uncertainty considering different levels of precision. Each decision maker's judgment on the performance of alternatives with respect to each criterion is expressed by qualitative linguistic labels. The new method takes into account linguistic data provided by the decision makers without any previous aggregation. Decision maker judgments are incorporated into the proposed method to generate a complete ranking of alternatives. An application in energy planning is presented as an illustrative case example in which energy policy alternatives are ranked. Seven energy alternatives under nine criteria were evaluated according to the opinion of three environmental and energy experts. The weights of the criteria are determined by fuzzy AHP, and the alternatives are ranked using qualitative TOPSIS. The proposed approach is compared with a modified fuzzy TOPSIS method, showing the advantages of the proposed approach when dealing with linguistic assessments to model uncertainty and imprecision. Although the new approach requires less cognitive effort to decision makers, it yields similar results.

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Decision‐Making in System Project, Planning, Operation, and Control: Motivation, Objectives, and Basic Concepts

Pedrycz

Ekel

Parreiras

2010

Fuzzy Multicriteria Decision‐Making

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A flexible consensus scheme for multicriteria group decision making under linguistic assessments

Cited by 213 publications

References 25 publications

Some Hybrid Geometric Aggregation Operators with 2-tuple Linguistic Information and Their Applications to Multi-attribute Group Decision Making

Some Hybrid Geometric Aggregation Operators with 2-tuple Linguistic Information and Their Applications to Multi-attribute Group Decision Making

Decision making under uncertainty using a qualitative TOPSIS method for selecting sustainable energy alternatives

Decision‐Making in System Project, Planning, Operation, and Control: Motivation, Objectives, and Basic Concepts

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