A dynamical consensus method based on exit–delegation mechanism for large group emergency decision making

Xu, Xuanhua; Zhong, Xiangyu; Chen, Xiaohong; Zhou, Yanju

doi:10.1016/j.knosys.2015.06.006

Cited by 125 publications

(58 citation statements)

References 59 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Compared to existing MAGEDM approaches 11,16,30,35,36,37,38 , the advantages of the proposed dynamic MAGEDM method are as follows:…”

Section: Discussionmentioning

confidence: 99%

“…Experts involved in MAGEDM problems featured by lack of information and time pressure might hesitate among several values when they provide their opinions, however, such a practical issue is neglected in existing MAGEDM approaches 11,16,30,35,36,37,38 . To fill the gap in current MAGEDM approaches, the proposed method has taken into account the experts' hesitation by using complex linguistic expressions based on HFLTS.…”

Section: Discussionmentioning

confidence: 99%

“…As far as we know, until now, no proposal in current MAGEDM approaches 35,36,37,38 considers the dynamic evolution of EEs dealing with both the updated information about alternatives and criteria along with the time and the experts' changes (quit or invited to join in the decision process), in addition to the modelling of experts' hesitancy due to uncertain information. Therefore, it is practically significant to address these issues in order to make satisfactory and reasonable decisions in real world MAGEDM problems.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A dynamic multi-attribute group emergency decision making method considering experts’ hesitation

Wang¹,

Rodríguez²,

Wang³

2018

IJCIS

View full text Add to dashboard Cite

Multi-attribute group emergency decision making (MAGEDM) has become a valuable research topic in the last few years due to its effectiveness and reliability in dealing with real-world emergency events (EEs). Dynamic evolution and uncertain information are remarkable features of EEs. The former means that information related to EEs is usually changing with time and the development of EEs. To make an effective and appropriate decision, such an important feature should be addressed during the emergency decision process; however, it has not yet been discussed in current MAGEDM problems. Uncertain information is a distinct feature of EEs, particularly in their early stage; hence, experts involved in a MAGEDM problem might hesitate when they provide their assessments on different alternatives concerning different criteria. Their hesitancy is a practical and inevitable issue, which plays an important role in dealing with EEs successfully, and should be also considered in real world MAGEDM problems. Nevertheless, it has been neglected in existing MAGEDM approaches. To manage such limitations, this study intends to propose a novel MAGEDM method that deals with not only the dynamic evolution of MAGEDM problems, but also takes into account uncertain information, including experts' hesitation. A case study is provided and comparisons with current approaches and related discussions are presented to illustrate the feasibility and validity of the proposed method.

show abstract

“…Compared to existing MAGEDM approaches 11,16,30,35,36,37,38 , the advantages of the proposed dynamic MAGEDM method are as follows:…”

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A dynamic multi-attribute group emergency decision making method considering experts’ hesitation

Wang¹,

Rodríguez²,

Wang³

2018

IJCIS

View full text Add to dashboard Cite

show abstract

“…Step 1: The optimized model of the weights of DMs is constructed by using Equation (8)~ (10). The iteration number is set as 1000, the optimization target value is eventually obtained as 6.467 as shown in Figure 2.…”

Section: Methodsmentioning

confidence: 99%

A Large Group Decision Making Approach Based on TOPSIS Framework with Unknown Weights Information

Lian

et al. 2017

MATEC Web Conf.

View full text Add to dashboard Cite

Abstract. Large group decision making considering multiple attributes is imperative in many decision areas. The weights of the decision makers (DMs) is difficult to obtain for the large number of DMs. To cope with this issue, an integrated multiple-attributes large group decision making framework is proposed in this article. The fuzziness and hesitation of the linguistic decision variables are described by interval-valued intuitionistic fuzzy sets. The weights of the DMs are optimized by constructing a non-linear programming model, in which the original decision matrices are aggregated by using the interval-valued intuitionistic fuzzy weighted average operator. By solving the non-linear programming model with MATLAB ® , the weights of the DMs and the fuzzy comprehensive decision matrix are determined. Then the weights of the criteria are calculated based on the information entropy theory. At last, the TOPSIS framework is employed to establish the decision process. The divergence between interval-valued intuitionistic fuzzy numbers is calculated by interval-valued intuitionistic fuzzy cross entropy. A real-world case study is constructed to elaborate the feasibility and effectiveness of the proposed methodology.Keywords. Multiple-attributes large group decision making, optimization of weights of DMs, non-linear programming model, TOPSIS.

show abstract

“…In addition, the consensus reaching process also has been employed to solve different application problems. For example, Xu et al [14] developed a dynamic consensus model for large-group emergency decision-making, in which an exit-delegation mechanism is utilized to handle clusters. Xu et al [15] presented a consensus model with the hesitant fuzzy preference relations and applied it to water allocation management.…”

Section: Consensus Reaching Processmentioning

confidence: 99%

Green Supplier Selection Based on Consensus Process and Integrating Prioritized Operator and Choquet Integral

Zhu

2018

Sustainability

View full text Add to dashboard Cite

Green supplier selection, as a core part of green supply chain management, has attracted the attention of various researchers in the past decade. Plenty of green supplier selection methods based on multi-criteria group decision-making have been presented in previous literature. However, these approaches ignore the consensus level between the experts, and they rarely consider the priority level among the experts and the interdependent relationship between criteria. To handle these issues, an integrated framework of green supplier selection under the hesitant fuzzy linguistic (HFL) environment was established. In this framework, the preference information expressed by HFL was transformed into the hesitant 2-tuple linguistic (H2TL). Then, the consensus process was introduced into the green supplier selection process to increase the consensus level between experts. The H2TL prioritized operator and Choquet integral operator were respectively applied to construct the group decision matrix and derive the ranking order of green suppliers. Finally, we used a numerical example to demonstrate the validity and applicability of the presented framework and implemented a comparative analysis to highlight the features of the presented method.

show abstract

A dynamical consensus method based on exit–delegation mechanism for large group emergency decision making

Cited by 125 publications

References 59 publications

A dynamic multi-attribute group emergency decision making method considering experts’ hesitation

A dynamic multi-attribute group emergency decision making method considering experts’ hesitation

A Large Group Decision Making Approach Based on TOPSIS Framework with Unknown Weights Information

Green Supplier Selection Based on Consensus Process and Integrating Prioritized Operator and Choquet Integral

Contact Info

Product

Resources

About