Consensus model of social network group decision-making based on trust relationship among experts and expert reliability

Due to people’s increasing dependence on social networks,it is essential to develop a consensus model considering not only their own factors but also the interaction between people.Both external trust relationship among experts and the internal reliability of experts are important factors in decision-making.This paper focuses on improving the scientificity and effectiveness of decision-making and presents a consensus model combining trust relationship among experts and expert reliability in social network group decision-making(SN-GDM).A concept named matching degree is proposed to measure expert reliability.Meanwhile,linguistic information is applied to manage the imprecise and vague information.Matching degree is expressed by a 2-tuple linguistic model,and experts’preferences are measured by a probabilistic linguistic term set(PLTS).Subsequently,a hybrid weight is explored to weigh experts’importance in a group.Then a consensus measure is introduced and a feedback mechanism is developed to produce some personalized recommendations with higher group consensus.Finally,a comparative example is provided to prove the scientificity and effectiveness of the proposed consensus model.

Maximum Group Perceived Utility Consensus Models Considering Regret Aversion

In the consensus-reaching process(CRP),the actual utility of decision-makers(DMs)is often influenced by the psychological behavior of regret aversion.However,the influence of regret aversion on DMs’utilities is rarely taken into account in the existing consensus models.The consensus-reaching problem of DMs with regret aversion is explored to maximize their perceived utilities under a limited budget.Firstly,three basic types of perceived utility functions are constructed based on the regret theory to describe the perceived utility of DMs with various preferences.Then,considering the limited budget and individual regret aversion,the maximum perceived utility consensus models based on types of left-skewed,right-skewed,middle-skewed,and heterogeneous utility preferences are proposed to achieve the consensus that maximizes the group perceived utility.After that,an example of land-transfer price negotiation in China is given to illustrate the validity of the proposed models.Finally,the model comparison and the sensitivity analysis are presented to reveal the influence of DMs’regret aversion on the CRP.The results suggest that the DMs’regret aversion will not affect left-skewed and right-skewed groups,but will affect the consensus results of middle-skewed and heterogeneous groups.

A Confidence-based Consensus Model for Multi-Attribute Group Decision Making:Exploring the Bounded Trust Propagation and Personalized Adjustment Willingness

Social trust network(STN)and minimum cost consensus(MCC)models have been widely used to address consensus issues in multi-attribute group decision-making(MAGDM)problems with limited resources.However,most researchers have overlooked the decision maker‘(DMs)’confidence levels(CLs)and adjustment willingness implicit in their evaluations.To address these problems,this paper explores a confidence-based MCC model that considers DMs’adjustment willingness in the STN.The proposed model includes several modifications to the traditional trust propagation and consensus optimization models.Firstly,the improved method for measuring CLs of DMs and the confidence-based normalization approach are defined,respectively.Secondly,the bounded trust propagation operator is proposed,which considers the credibility of mediators to complete the STN.Thirdly,the identification rules based on the consensus index and CL are defined,and the MCC model with personalized cost functions and acceptable adjustment thresholds is built to automatically generate adjustment values for non-consensus DMs.Finally,a model to identify the non-cooperative behavior at the element level is established and the hybrid MCC model with persuasion strategies is provided.Finally,a case study is processed to verify the applicability of the proposed model,and comparison and sensitivity analysis are conducted to highlight its benefits.

Consensus Hologram QSAR Model Studying on the Aqueous Hydroxyl Radical Oxidation Reaction Rate Constants of Organic Micropollutants

The combination of hologram quantitative structure-activity relationship(HQSAR)and consensus modeling was employed to study the quantitative structure-property relationship(QSPR)model for calculating the aqueous hydroxyl radical oxidation reaction rate constants(kOH)of organic micropollutants(OMPs).Firstly,individual HQSAR model were established by using standard HQSAR method.The optimal individual HQSAR model was obtained while setting the parameter of fragment distinction and fragment size to“B”and“3~6”respectively.Secondly,consensus HQSAR model was established by building the regression model between the kOH and the hologram descriptors with consensus partial least-squares(cPLS)approach.The obtained individual and consensus HQSAR model were validated with a randomly selected external test set.The result of external test set validation demonstrates that both individual and consensus HQSAR model are available for predicting the kOH of OMPs.Compared with the optimal individual HQSAR model,the established consensus HQSAR model shows higher prediction accuracy and robustness.It is shown that the combination of HQSAR and consensus modeling is a practicable and promising method for studying and predicting the kOH of OMPs.

A Lifting Method for Krause's Consensus Model

In this work,we aim to show how to solve the continuous-time and continuous-space Krause model by using high-order finite difference(FD)schemes.Since the considered model admits solutions withδ-singularities,the FD method cannot be applied directly.To deal with the annoyingδ-singulariti-es,we propose to lift the solution space by introducing a spltting method,such that theδ-singularities in one spatial direction become step functions with dis-continuities.Thus the traditional shock-capturing FD schemes can be applied directly.In particular,we focus on the two dimensional case and apply a fifth-order weighted nonlinear compact scheme(WCNS)to ilustrate the validity of the proposed method.Some technical details for implementation are also presented.Numerical results show that the proposed method can captureδ-singularities well,and the obtained number of delta peaks agrees with the the-oretical prediction in the literature.

Large-Scale Group Decision Making:A Systematic Review and a Critical Analysis

The society in the digital transformation era demands new decision schemes such as e-democracy or based on social media.Such novel decision schemes require the participation of many experts/decision makers/stakeholders in the decision processes.As a result,large-scale group decision making(LSGDM)has attracted the attention of many researchers in the last decade and many studies have been conducted in order to face the challenges associated with the topic.Therefore,this paper aims at reviewing the most relevant studies about LSGDM,identifying the most profitable research trends and analyzing them from a critical point of view.To do so,the Web of Science database has been consulted by using different searches.From these results a total of 241 contributions were found and a selection process regarding language,type of contribution and actual relation with the studied topic was then carried out.The 87 contributions finally selected for this review have been analyzed from four points of view that have been highly remarked in the topic,such as the preference structure in which decision-makers’opinions are modeled,the group decision rules used to define the decision making process,the techniques applied to verify the quality of these models and their applications to real world problems solving.Afterwards,a critical analysis of the main limitations of the existing proposals is developed.Finally,taking into account these limitations,new research lines for LSGDM are proposed and the main challenges are stressed out.