A Linguistic Large Group Decision Making Method Based on the Cloud Model

Wang, Pei; Xu, Xuanhua; Huang, Shuai; Cai, Chenguang

doi:10.1109/tfuzz.2018.2822242

Cited by 122 publications

(50 citation statements)

References 35 publications

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“…Some integration methods also consider the preference information to determine subgroup weights. Wang et al [11] developed a hybrid weight scheme to obtain the cluster weight vector, which took both the subgroup size and the variance into consideration. Ma et al [38] employed cluster size and cluster reliability that was obtained on the basis of cluster similarity and cluster certainty as measure indicators of the hybrid cluster weight.…”

Section: Collective Decision Matrix Generation In Lsgdmmentioning

confidence: 99%

“…The growth of LSGDM is stimulated by the rapid development and innovation of social networks, which provides an available information exchange platform for a tremendous number of stakeholders to participate in the decision making process with modest cost and time spent [7,8]. The popularity of LSGDM has attracted the attention of lots of scholars [9][10][11][12]. These researches divided LSGDM problems into four important phases, considered as expert classification, consensus reaching processes (CRPs), collective decision matrix generation, and decision making method.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Bid Evaluation for Major Construction Projects Under Large-Scale Group Decision-Making Environment and Characterized Expertise Levels

Xiao¹,

Chen²,

Zhang³

et al. 2020

IJCIS

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Rapid growth and development of civil engineering in recent years inspire building enterprises to concentrate on construction contractor selection for achieving more construction quality and lower construction cost. The existing studies generally regard the process of selecting the best contractor as a multi-criteria group decision making problem. Few research studies addressed the contractor selection problem in the context of large-scale group decision making, which is common in practical scenarios in terms of major construction projects as a number of experts with diverse backgrounds are usually involved. On this basis, we establish a contractor selection framework under large-scale group decision making environment, which covers expert classification, consensus reaching process, collective decision matrix generation, and the ranking-oriented decision making method. We cluster expert group with K-means clustering method based on expertise levels, which are depicted by six features generated with an expertise identification approach. The consensus model manages consensus reaching process from both intra-and interlayers and takes into account the interactions between them. After reaching agreements among experts, this paper utilizes the concept of proportional hesitant fuzzy linguistic term set to assemble intra-subgroup assessments for the reduction of information loss or distortion. Then, an aggregation process carries on as to gather subgroup assessments in which the subgroup weights are derived from their cluster centers and sizes in the use of the TOPSIS method. Finally, the well-established decision making tool integrating qualitative and quantitative criteria, ELECTRE III, is adapted to elicit the ranking of bidders. An illustrative study and a comparative analysis are performed to demonstrate the feasibility and effectiveness of the established multi-criteria group decision making approach.

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Section: Collective Decision Matrix Generation In Lsgdmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Bid Evaluation for Major Construction Projects Under Large-Scale Group Decision-Making Environment and Characterized Expertise Levels

Xiao¹,

Chen²,

Zhang³

et al. 2020

IJCIS

View full text Add to dashboard Cite

show abstract

“…Decision making trial and evaluation laboratory (DEMATEL) was first proposed by American scholars A. Gabus and E. Fontela. In recent years, it has developed into a method for analysing the relationships among multiple factors influencing complex problems . Through the study of the characteristics of CES, this study improves the DEMATEL method to make it more suitable for CES and improve the accuracy of its results.…”

Section: Comprehensive Reliability Evaluation Based On Similarity Of mentioning

confidence: 99%

“…In recent years, it has developed into a method for analysing the relationships among multiple factors influencing complex problems. 46 Through the study of the characteristics of CES, this study improves the DEMATEL method to make it more suitable for CES and improve the accuracy of its results. The algorithmic steps are as follows: Step 1.…”

Section: Correlation Analysis Of Failure Modesmentioning

confidence: 99%

Comprehensive reliability evaluation of multistate complex electromechanical systems based on similarity of cloud models

Wang

Gao

et al. 2020

Quality & Reliability Eng

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High reliability and security have become the hallmarks of complex electromechanical systems. Owing to the difficulties in fault data collection, ambiguity and uncertainty have been inevitably associated with complex electromechanical systems. Thus, the ability to perform reliability evaluation using scarce fault data is of immense significance to these machines and is the focus of this study. A similarity based cloud model is proposed to evaluate the running state of complex electromechanical systems. By combining objective and subjective factors, the reliability of complex electromechanical systems is evaluated by calculating the similarity between the cloud models of actual and standardised states. Next, the inverter of an offshore wind turbine is used to verify the accuracy and effectiveness of the proposed approach. The cloud model based framework for reliability evaluation inherits the preponderance of the uncertainty problem, overcomes the drawbacks of the current reliability approaches, and provides a theoretical basis, as well as a practical approach for the maintenance and repair of complex electromechanical systems with missing fault data. Additionally, it also provides a new methodology for solving the uncertainty problems caused by paucity of data.

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“…Wu et al [ 14 ] designed an applicable method using cloud model with 2-order additive fuzzy measures for the selection of waste-to-energy disposal sites in China. Wang et al [ 15 ] suggested a consensus-based method based on cloud model for the large group decision making with linguistic information. In addition, Liu et al [ 16 ] used a grey relational analysis method and cloud model to evaluate failure modes with incomplete weight information of risk factors.…”

Section: Introductionmentioning

confidence: 99%

Robot Evaluation and Selection with Entropy-Based Combination Weighting and Cloud TODIM Approach

Wang

Miao

Cui

et al. 2018

Entropy

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Nowadays robots have been commonly adopted in various manufacturing industries to improve product quality and productivity. The selection of the best robot to suit a specific production setting is a difficult decision making task for manufacturers because of the increase in complexity and number of robot systems. In this paper, we explore two key issues of robot evaluation and selection: the representation of decision makers' diversified assessments and the determination of the ranking of available robots. Specifically, a decision support model which utilizes cloud model and TODIM (an acronym in Portuguese of interactive and multiple criteria decision making) method is developed for the purpose of handling robot selection problems with hesitant linguistic information. Besides, we use an entropy-based combination weighting technique to estimate the weights of evaluation criteria. Finally, we illustrate the proposed cloud TODIM approach with a robot selection example for an automobile manufacturer, and further validate its effectiveness and benefits via a comparative analysis. The results show that the proposed robot selection model has some unique advantages, which is more realistic and flexible for robot selection under a complex and uncertain environment.

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A Linguistic Large Group Decision Making Method Based on the Cloud Model

Cited by 122 publications

References 35 publications

Bid Evaluation for Major Construction Projects Under Large-Scale Group Decision-Making Environment and Characterized Expertise Levels

Bid Evaluation for Major Construction Projects Under Large-Scale Group Decision-Making Environment and Characterized Expertise Levels

Comprehensive reliability evaluation of multistate complex electromechanical systems based on similarity of cloud models

Robot Evaluation and Selection with Entropy-Based Combination Weighting and Cloud TODIM Approach

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