Group decision making with incomplete information: a dominance and quasi‐optimality volume‐based approach using Monte‐Carlo simulation

Sarabando, Paula; Dias, Luís C.; Vetschera, Rudolf

doi:10.1111/itor.12315

Cited by 10 publications

(4 citation statements)

References 53 publications

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“…In the near future, we shall pay attention to the consensus reaching process and how to deal with the situations when criteria weights are incompletely known [77][78][79][80][81][82].…”

Section: Discussionmentioning

confidence: 99%

Research on the English Classroom Teaching Effect Evaluation with Interval-Valued Intuitionistic Fuzzy Grey Relational Analysis Method

Zhang

2022

Mathematical Problems in Engineering

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The English classroom teaching effect evaluation is looked as the multiattribute group decision-making (MAGDM). Thus, a useful MAGDM algorithm is needed to cope with it. Depending on the classical GRA process and interval-valued IFSs (IVIFSs), this study builds the IVIF-GRA process to assess the English classroom teaching effect. First of all, the concepts of IVIFSs are reviewed. In addition, the weights of criteria are derived through the CRITIC method. Afterwards, the GRA model is extended to IVIFSs to get the final result of the alternative. Therefore, all alternatives could be ranked and the optimal one with English classroom teaching effect can be identified. At last, a given numerical example and some given comparative studies are obtained. The analysis results show that the defined algorithms are effective for solving the English classroom teaching effect evaluation.

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“…In the near future, we shall pay attention to the consensus reaching process and how to deal with the situations when criteria weights are incompletely known [77][78][79][80][81][82].…”

Section: Discussionmentioning

confidence: 99%

Research on the English Classroom Teaching Effect Evaluation with Interval-Valued Intuitionistic Fuzzy Grey Relational Analysis Method

Zhang

2022

Mathematical Problems in Engineering

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“…This results in incomplete FPRs where missing values have to be estimated. Several methods have been proposed so far for this purpose, like the ones in [20][29]- [35]. In particular, we focus on the model discussed in [30] because missing values are estimated combining additive reciprocity and additive transitivity properties.…”

Section: A Dealing With Incomplete Informationmentioning

confidence: 99%

Fuzzy Group Decision Making With Incomplete Information Guided by Social Influence

Capuano

Chiclana

Fujita

et al. 2018

IEEE Trans. Fuzzy Syst.

277

106

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A promising research area in the field of Group Decision Making (GDM) is the study of interpersonal influence and its impact on the evolution of experts' opinions. In conventional GDM models, a group of experts express their individual preferences on a finite set of alternatives, then preferences are aggregated and the best alternative, satisfying the majority of experts, is selected. Nevertheless, in real situations, experts form their opinions in a complex interpersonal environment where preferences are liable to change due to social influence. In order to take into account the effects of social influence during the GDM process, we propose a new influence-guided GDM model based on the following assumptions: experts influence each other and the more an expert trusts in another expert, the more his opinion is influenced by that expert. The effects of social influence are especially relevant to cases when, due to domain complexity, limited expertise or pressure to make a decision, an expert is unable to express preferences on some alternatives, i.e. in presence of incomplete information. The proposed model adopts fuzzy rankings to collect both experts' preferences on available alternatives and trust statements on other experts. Starting from collected information, possibly incomplete, the configuration and the strengths of interpersonal influences are evaluated and represented through a Social Influence Network (SIN). The SIN, in its turn, is used to estimate missing preferences and evolve them by simulating the effects of experts' interpersonal influence before aggregating them for the selection of the best alternative. The proposed model has been experimented with synthetic data to demonstrate the influence driven evolution of opinions and its convergence properties.

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“…Moreover, the methods proposed here can be used in other contexts that use utility functions, such as decision trees, game theory and negotiation analysis, where simulation approaches can also be used to inform decision making. For instance, Sarabando et al (2019) proposed the use of simulation to help a mediator propose agreements in bilateral negotiations, with uncertainty about the utilities of the negotiating parties.…”

Section: Introductionmentioning

confidence: 99%

On generating utility functions in Stochastic Multicriteria Acceptability Analysis

Dias

Vetschera

2019

European Journal of Operational Research

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Group decision making with incomplete information: a dominance and quasi‐optimality volume‐based approach using Monte‐Carlo simulation

Cited by 10 publications

References 53 publications

Research on the English Classroom Teaching Effect Evaluation with Interval-Valued Intuitionistic Fuzzy Grey Relational Analysis Method

Research on the English Classroom Teaching Effect Evaluation with Interval-Valued Intuitionistic Fuzzy Grey Relational Analysis Method

Fuzzy Group Decision Making With Incomplete Information Guided by Social Influence

On generating utility functions in Stochastic Multicriteria Acceptability Analysis

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