Approaches to group decision making with linguistic preference relations based on multiplicative consistency

Jin, Feifei; Ni, Zhiwei; Pei, Lidan; Chen, Huayou; Zhu, Xuhui; Ni, Liping

doi:10.1016/j.cie.2017.10.008

Cited by 28 publications

(21 citation statements)

References 37 publications

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“…Jin et al [40] proposed the definition of multiplicative consistent linguistic preference relation based on the multiplicative consistency of fuzzy preference relation as follows:…”

Section: -Tuple Flpr and Multiplicative Consistency Of Flprmentioning

confidence: 99%

Consensus Constructing in Large-Scale Group Decision Making With Multi-Granular Probabilistic 2-Tuple Fuzzy Linguistic Preference Relations

Song

2019

IEEE Access

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As the number of participants involves in decisions getting complex and the heterogeneity could be produced among decision makers, a large-scale group decision making (LGDM) method with consensus constructing need to be considered. In order to demonstrate the complex relationship and reduce heterogeneity among decision makers, a consensus process of LGDM is proposed in this paper, in which multi-granular probabilistic fuzzy linguistic preference relations (MGPFLPRs) are used to represent subgroup's preferences information. First, mathematical programming is proposed to deal with MGPFLPR based on expected multiplicative consistency and obtain the priority weight vector. Second, collective priority weights of alternative are obtained by fusing sub-group's priority weights of alternative based on the weighted averaging operator. Then, an automatic iteration consensus reaching algorithm is implemented for the purpose of reaching a consensus in LGDM with MGPFLPRs. Finally, an emergency decision problem is applied to demonstrate the effectiveness of the proposed method.

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“…Jin et al [40] proposed the definition of multiplicative consistent linguistic preference relation based on the multiplicative consistency of fuzzy preference relation as follows:…”

Section: -Tuple Flpr and Multiplicative Consistency Of Flprmentioning

confidence: 99%

Consensus Constructing in Large-Scale Group Decision Making With Multi-Granular Probabilistic 2-Tuple Fuzzy Linguistic Preference Relations

Song

2019

IEEE Access

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“…In a group decision-making (GDM) problem, preference relations (PRs) are widely used tools for comparing two alternatives at a time. [1][2][3][4][5][6][7][8] PRs provide efficient ways to represent the preference levels of the experts by integrating two alternatives in pairs. Some PRs are formed in the last few decades based on various information representation types.…”

Section: Introductionmentioning

confidence: 99%

Multiplicative consistency analysis of linguistic preference relation with self‐confidence level and self‐doubting level and its application in a group decision making

Mandal

Samanta²,

Pal

2021

Int J Intell Syst

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“…(2) Compared to the specific evaluation values, natural languages such as “excellent”, “good” or “bad” are more intuitive for representing the opinions of decision makers. Therefore, preference information decision analysis methods based on linguistic form have emerged (Jin et al, ; Liu & Chen, ), especially fuzzy linguistic decision‐making, which has been widely studied recently (Liu, Liu, & Merigó, ). These work on group decision‐making focus on collecting the judgement preferences of group experts and decision aggregation matrix based on operators, but ignore the influence of group interaction and affective state on decision preferences, making the discussion of decision‐making consistency easily deviate from the true wishes of group experts.…”

Section: Introductionmentioning

confidence: 99%

A multi‐agent affective interactive MAGDM approach and its applications

Peng

Sangwoo

2019

Expert Systems

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Traditional multi‐attribute group decision‐making (MAGDM) methods focus on weights calculation of sub‐attributes and experts' preferences, but lack the discussion on the decision‐makers' affective interaction, and its influence on the decision preference and group consistency. To address this problem, the present study proposed a new multilayer affective computing model based on “personality–mood–emotion” pattern, under the multi‐agent decision system framework. In addition, we introduced the group trending index and affection‐preference incentive mechanism, which can help simulate MAGDM process and learn group experts' decision preferences. Further, we proposed a new multi‐agent affective interactive MAGDM (MAAI‐MAGDM) method, where we defined a novel group convergence index and an alternative decision entropy to explain the convergence process of decision and group consistency. Compared to the traditional MAGDM approaches, the proposed MAAI‐MAGDM method fully considered the affective features of each expert, reduced the dependence on aggregation operators and weight analysis, alleviated the workload of group experts, and effectively reduced the complexity of decision‐making calculation process. Finally, we verified that the proposed method can effectively assist the decision‐making processes by employing two numerical cases.

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Approaches to group decision making with linguistic preference relations based on multiplicative consistency

Cited by 28 publications

References 37 publications

Consensus Constructing in Large-Scale Group Decision Making With Multi-Granular Probabilistic 2-Tuple Fuzzy Linguistic Preference Relations

Consensus Constructing in Large-Scale Group Decision Making With Multi-Granular Probabilistic 2-Tuple Fuzzy Linguistic Preference Relations

Multiplicative consistency analysis of linguistic preference relation with self‐confidence level and self‐doubting level and its application in a group decision making

A multi‐agent affective interactive MAGDM approach and its applications

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