The minimum cost consensus model considering the implicit trust of opinions similarities in social network group decision‐making

Wu, Tong; Liu, Xinwang; Gong, Zaiwu; Zhang, Huan‐Huan; Herrera, Francisco

doi:10.1002/int.22214

Cited by 41 publications

(5 citation statements)

References 43 publications

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“…On the one hand, Zha et al 36 constructed a bounded confidence model by using the similarity, where expert

e^{t}

will be recommended to

e^{t'}

as a reference for preference adjustment if their similarity is greater than his/her bounded confidence, and then the model was applied to the feedback mechanism. Wu et al 57 gave the definition of implicit trust based on the similarity measure and explored the effects of trust on the consensus model. Some studies can be referred to References [58–60], which can provide theoretical support for the proposed method.…”

Section: Numerical Examplementioning

confidence: 99%

An extended VIKOR method based on particle swarm optimization and novel operations of probabilistic linguistic term sets for multicriteria group decision‐making problem

Liu

Yang

2022

Int J of Intelligent Sys

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This paper proposes an extended VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR) method based on the particle swarm optimization (PSO) algorithm for solving multicriteria group decision-making problems with probabilistic linguistic information. First, we define the novel operations of probabilistic linguistic term sets and then prove the corresponding properties.Second, we apply a modified PSO algorithm to the consensus reaching process to improve the collective consensus level. In the context of probabilistic linguistic information, each participant can be recognized as a particle moving towards the best position. The consensus level can be regarded as the objective function that is used to construct the fitness function. In the update function, the trust relationship and the similarity measure between experts are exploited to determine the adjustment coefficient. The new consensus model based on PSO can ensure that the ultimate evaluation achieves a high level of consensus. Afterward, we propose the extended VIKOR method to obtain the optimal solution, which not only avoids the loss of decision information, but also considers the separation of each alternative from the positive ideal solution and the negative ideal solution when criteria are interactive. The advantages of

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“…On the one hand, Zha et al 36 constructed a bounded confidence model by using the similarity, where expert

e^{t}

will be recommended to

e^{t'}

Section: Numerical Examplementioning

confidence: 99%

An extended VIKOR method based on particle swarm optimization and novel operations of probabilistic linguistic term sets for multicriteria group decision‐making problem

Liu

Yang

2022

Int J of Intelligent Sys

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“…Liu et al (2017) developed a trust induced recommendation mechanism to generate personalised advice for the inconsistent experts to reach higher consensus degree. Wu et al (2020) explored the effects of trust on consensus and some minimum cost consensus models are proposed based on implicit trust between individuals and the moderator. Although above trust-based feedback mechanism avoided the inconsistent DMs are forced to accept the recommended advices, the CRP are still time consuming and costly because the final evaluations are obtained after multi-round dynamic interaction.…”

Section: Introducementioning

confidence: 99%

A novel consensus reaching method for MCGDM in social network with intuitionistic grey linguistic numbers

Guo

Li²,

Jing³

2022

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PurposeThe existing consensus reaching mechanisms ignore the influence of social triangle structure on the decision-makers’ (DMs') weights, and the consensus reaching process (CRP) fails to fully reflect the DMs' subjectivity and can be time consuming and costly. To solve these issues, a novel CRP for multi-criteria group decision-making (MCGDM) problems with intuitionistic grey linguistic numbers (IGLNs) is proposed in this paper.Design/methodology/approachFirst, a weight calculation method is proposed by analysing the triangle structure of DMs' social network and scale of adjacent nodes. Then, a consensus degree index based on three-level polygon area is defined and applied to identify the inconsistent DMs. Finally, the feedback mechanism based on particle swarm optimisation (PSO) algorithm under grey linguistic environment is developed, where subjective trust relationships in social network is utilised to determine the adjustment coefficient.FindingsThe advantages of the proposed method are highlighted by two practical applications of the evaluation of tunnel construction method and the selection of a hotel for the centralised isolation. Comparision analysis and numerical simulation are performed to reveal the effectiveness and applicability of the method.Practical implicationsThe proposed model can not only reflect the effect of triangle structure in social network on DMs' weights, but also reduce the time and cost of decision-making.Originality/valueThe main contribution of this paper is to propose a new MCGDM model based on intuitionistic grey linguistic numbers, which can handle the problem of inconsistency of information more effectively.

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“…With the in-depth study of the SNGDM problem, more and more researchers have begun to pay attention to the trust relationship between DMs. The weight of experts is calculated by constructing the trust relationship matrix between experts (Wu and Chiclana, 2014a, b;Wu et al, 2019a). In order to better simulate the situation where there is no direct social relationship between DMs in real life, some studies have introduced the trust propagation operator to express the process of indirect establishment of trust relationship between DMs (Yang et al, 2021;Wu et al, 2016Wu et al, , 2017Wu et al, , 2021aUreña et al, 2019a, b).…”

Section: Introductionmentioning

confidence: 99%

Visual social network group consensus method with improved PageRank algorithm

Fan

Wang

2022

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PurposeThe purpose of this study is to build a consensus model of social network group decision-making (SNGDM) based on improved PageRank algorithm. By objectively and fairly measuring the evaluation ability of participants in the decision-making process, the authors can improve the fairness and authenticity of the weight solution of decision-makers (DM) in the decision-making process. This ensures the reliability of the final group consensus results.Design/methodology/approachThis study mainly includes six parts: preference expression, calculation of DM's weight, preference aggregation, consensus measurement, opinion adjustment and alternative selection. First, Pythagorean fuzzy expression is introduced to express the preference of DMs, which expands the scope of preference expression of DMs. Second, based on the social network structure among DMs, the process of “mutual judgment” among DMs is increased to measure the evaluation ability of DMs. On this basis, the PageRank algorithm is improved to calculate the weight of DMs. This makes the process of reaching consensus more objective and fair. Third, in order to minimize the evaluation difference between groups and individuals, a preference aggregation model based on plant growth simulation algorithm (PGSA) is proposed to aggregate group preferences. Fourth, the consensus index of DMs is calculated from three levels to judge whether the consensus degree reaches the preset value. Fifth, considering the interaction of DMs in the social network, the evaluation value to achieve the required consensus degree is adjusted according to the DeGroot model to obtain the overall consensus. Finally, taking the group preference as the reference, the ranking of alternatives is determined by using the Pythagorean fuzzy score function.FindingsThis paper proposes a consensus model of SNGDM based on improved PageRank algorithm to aggregate expert preference information. A numerical case of product evaluation is introduced, and the feasibility and effectiveness of the model are explained through sensitivity analysis and comparative analysis. The results show that this method can solve the problem of reaching consensus in SNGDM.Originality/valueDifferent DMs may have different judgment criteria for the same decision-making problem, and the angle and depth of considering the problem will also be different. By increasing the process of mutual evaluation of DMs, the evaluation ability of each DM is judged only from the decision-making problem itself. In this way, the evaluation opinions recognized by most DMs will form the mainstream of opinions, and the influence of corresponding DMs will increase. Therefore, in order to improve the fairness and reliability of the consensus process, this study measures the real evaluation ability of DMs by increasing the “mutual judgment” process. On this basis, the defect of equal treatment of PageRank algorithm in calculating the weight of DMs is improved. This ensures the authenticity and objectivity of the weight of DMs. That is to improve the effectiveness of the whole evaluation mechanism. This method considers both the influence of DMs in the social network and their own evaluation level. The weight of DMs is calculated from two aspects: sociality and professionalism. It provides a new method and perspective for the calculation of DM’s weight in SNGDM.

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The minimum cost consensus model considering the implicit trust of opinions similarities in social network group decision‐making

Cited by 41 publications

References 43 publications

An extended VIKOR method based on particle swarm optimization and novel operations of probabilistic linguistic term sets for multicriteria group decision‐making problem

An extended VIKOR method based on particle swarm optimization and novel operations of probabilistic linguistic term sets for multicriteria group decision‐making problem

A novel consensus reaching method for MCGDM in social network with intuitionistic grey linguistic numbers

Visual social network group consensus method with improved PageRank algorithm

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