A cohesion-driven consensus reaching process for large scale group decision making under a hesitant fuzzy linguistic term sets environment

Rodríguez, Rosa M.; Labella, Álvaro; Sesma‐Sara, Mikel; Bustince, Humberto; Martínez, Luis

doi:10.1016/j.cie.2021.107158

Cited by 75 publications

(24 citation statements)

References 64 publications

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“…To approach this issue, many studies have utilized the consensus method [ 62 – 64 ], consistency index [ 21 , 54 , 60 ], and expert weighting method [ 5 , 65 ] to reach a consensus or eliminate conflict in the EDM process. In the future, it would be interesting to consider decision-makers’ bounded confidence [ 75 ], knowledge structures [ 17 ], sub-group cohesiveness [ 42 ], opinions evolution [ 9 ], and dynamic trust [ 49 ] during the consensus reaching process in EDM.…”

Section: Challenges and Future Directionsmentioning

confidence: 99%

“…In this paper, a risk decision analysis method based on CPT was proposed to solve the risk decision-making problem in emergency response. The topic of red cluster is fuzzy sets and linguistic variables, in which the paper of [69] is the most influential article and has the largest number of links (42). The concept of linguistic variables and their application to approximate reasoning were described in detail in Ref.…”

Section: Document Citation and Co-citation Analysismentioning

confidence: 99%

“…To approach this issue, many studies have utilized the consensus method [62][63][64], consistency index [21,54,60], and expert weighting method [5,65] to reach a consensus or eliminate conflict in the EDM process. In the future, it would be interesting to consider decision-makers' bounded confidence [75], knowledge structures [17], sub-group cohesiveness [42], opinions evolution [9], and dynamic trust [49] during the consensus reaching process in EDM. (3) Many researches have been conducted by extending the classic MCDM methods in EDM, such as the prospect theory [35,51,52], the TOPSIS [6,45], the TODIM [33,34], the analytic network process (ANP) [79], and the combinative distance-based assessment (CODAS) [39].…”

Section: Future Directionsmentioning

confidence: 99%

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Decades on emergency decision-making: a bibliometric analysis and literature review

Hou

Mao

Liu

et al. 2021

Complex Intell. Syst.

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When an emergency occurs, effective decisions should be made in a limited time to reduce the casualties and economic losses as much as possible. In the past decades, emergency decision-making (EDM) has become a research hotspot and a lot of studies have been conducted for better managing emergency events under tight time constraint. However, there is a lack of a comprehensive bibliometric analysis of the literature on this topic. The objective of this paper is to provide academic community with a complete bibliometric analysis of the EDM researches to generate a global picture of developments, focus areas, and trends in the field. A total of 303 journal publications published between 2010 and 2020 were identified and analyzed using the VOSviewer in regard to cooperation network, co-citation network, and keyword co-occurrence network. The findings indicate that the annual publications in this research field have increased rapidly since 2014. Based on the cooperation network and co-citation network analyses, the most productive and influential countries, institutions, researchers, and their cooperation networks were identified. Using the co-citation network analysis, the landmark articles and the core journals in the EDM area are found out. With the help of the keyword co-occurrence network analysis, research hotspots and development of the EDM domain are determined. According to current trends and blind spots in the literature, possible directions for further investigation are finally suggested for EDM. The literature review results provide valuable information and new insights for both scholars and practitioners to grasp the current situation, hotspots and future research agenda of the EDM field.

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Section: Challenges and Future Directionsmentioning

confidence: 99%

Section: Document Citation and Co-citation Analysismentioning

confidence: 99%

Section: Future Directionsmentioning

confidence: 99%

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Decades on emergency decision-making: a bibliometric analysis and literature review

Hou

Mao

Liu

et al. 2021

Complex Intell. Syst.

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“…GDM aims to reconcile differences of preferences articulated by multiple decision makers or experts to find an alternative or a subset of alternatives with acceptable group agreement [1,2]. In recent years, with the rapid development of information technology, the number of participants allowed to take part in a decision-making activity drastically increases, which has led to the so-called large-scale group decision-making (LSGDM) to become a new type of GDM [3][4][5][6][7][8][9][10][11][12][13][14][15]. Generally, a GDM problem has been considered as a LSGDM problem when the number of experts engaged in the decision process is no fewer than 20 [16].…”

Section: Introductionmentioning

confidence: 99%

“…Xu et al [19] proposed a consensus model for multi-attribute LSGDM to manage experts' minority opinions and non-cooperative behaviors. In the past few years, some CRP models have been proposed to deal with LSGDM problems in linguistic environment [13,63,64].…”

Section: Introductionmentioning

confidence: 99%

An Influence Network-Based Consensus Model for Large-Scale Group Decision Making with Linguistic Information

Yao

2022

Int J Comput Intell Syst

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The vast majority of the existing social network-based group decision-making models require extra information such as trust/distrust, influence and so on. However, in practical decision-making process, it is difficult to get additional information apart from opinions of decision makers. For large-scale group decision making (LSGDM) problem in which decision makers articulate their preferences in the form of comparative linguistic expressions, this paper proposes a consensus model based on an influence network which is inferred directly from preference information. First, a modified agglomerative hierarchical clustering algorithm is developed to detect subgroups in LSGDM problem with flexible linguistic information. Meanwhile, a measure method of group consensus level is proposed and the optimal clustering level can be determined. Second, according to the preference information of group members, influence network is constructed by determining intra-cluster and inter-cluster influence relationships. Third, a two-stage feedback mechanism guided by influence network is established for the consensus reaching process, which adopts cluster adjustment strategy and individual adjustment strategy depending on the different levels of group consensus. The proposed mechanism can not only effectively improve the efficiency of consensus reaching of LSGDM, but also take individual preference adjustment into account. Finally, the feasibility and effectiveness of the proposed method are verified by the case of intelligent environmental protection project location decision.

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Information consistent degree‐based clustering method for large‐scale group decision‐making with linear uncertainty distributions information

Gong

Wei

et al. 2021

Int J of Intelligent Sys

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Clustering analysis is a key technique in reducing the dimensionality of high volume irregular data containing large‐scale group decision‐making (LSGDM) information. Uncertainty theory is suitable for subjective estimation or situation, such as lack of historical data, and it can be employed to effectively express the uncertainty of trust and preference information in LSGDM problems. This paper studies the dimensionality reduction and subgroup optimization in LSGDM by utilizing linear uncertain variables in social networks. A clustering method is proposed to decompose the large group into several subgroups of higher consilience degrees and higher preference similarities, and lower the dimension of information for LSGDM. In the clustering process, two measurement attributes, trust relationship and preference relationship of decision‐makers, are combined, and information consistent degree is utilized as the clustering indicator. This approach does not need to preset the threshold and the number of subgroups, and can be employed to obtain subgroups with similar preferences and stable trust relationship. Through the clustering reliability evaluation of subgroups, the rationality of large‐scale group clustering results is verified. Subgroup consensus contribution is used to identify superior subgroups and quantify the role of subgroups in improving the consensus level. An example of emergency decision‐making and comparative analysis is provided to explain the feasibility and advantages of the proposed method.

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A cohesion-driven consensus reaching process for large scale group decision making under a hesitant fuzzy linguistic term sets environment

Cited by 75 publications

References 64 publications

Decades on emergency decision-making: a bibliometric analysis and literature review

Decades on emergency decision-making: a bibliometric analysis and literature review

An Influence Network-Based Consensus Model for Large-Scale Group Decision Making with Linguistic Information

Information consistent degree‐based clustering method for large‐scale group decision‐making with linear uncertainty distributions information

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