A consensus model for large-scale group decision making with hesitant fuzzy information and changeable clusters

Wu, Zhibin; Xu, Jiuping

doi:10.1016/j.inffus.2017.09.011

Cited by 334 publications

(121 citation statements)

References 57 publications

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“…Basically, the idea of clustering is grouping similar objects into the same cluster, while less-similar objects should be in different cluster. Since the objective of clustering is to splita finite unlabeled dataset into a number of subsets so that it is exploratory in nature [105]. Many types of clustering techniques have been discussed by Faber et al [104].…”

Section: Clustering Analysis For Decision-makingmentioning

confidence: 99%

“…Furthermore, Wu and Xu [105] have used clustering method to change the decision-makers' provided preferences by using fuzzy preference relations in order to break down the larger problem into smaller pieces. They have identified the subgroups in which members have similar preferences [105].…”

Section: Clustering Analysis For Decision-makingmentioning

confidence: 99%

“…They have identified the subgroups in which members have similar preferences [105]. Finally, by using clustering analysis, Delaney et al [109] could identify influences on decision-making processes based on the age and gender differences.…”

Section: Clustering Analysis For Decision-makingmentioning

confidence: 99%

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Customer Purchasing Behavior Analysis as Alternatives for Supporting In-Store Green Marketing Decision-Making

2017

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Due to increasing concerns about environmental protection, the environmental sustainability of businesses has been widely considered in the manufacturing and supply chain context. Further, its adoption has been implemented in the retail industry for marketing field, including green product promotion. This study aimed to propose a customer purchasing behavior analysis as an alternative for supporting decision-making in order to promote green products in retail stores. Hence, right-on-target marketing strategies can be implemented appropriately. The study was carried out using shopping path data collected by radio frequency identification (RFID) from a large retail store in Seoul, South Korea. In addition, the store layout and its traffic were also analyzed. This method is expected to help experts providing appropriate decision alternatives. In addition, it can help retailers in order to increase product sales and achieve high levels of customer satisfaction.

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Section: Clustering Analysis For Decision-makingmentioning

confidence: 99%

Section: Clustering Analysis For Decision-makingmentioning

confidence: 99%

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Customer Purchasing Behavior Analysis as Alternatives for Supporting In-Store Green Marketing Decision-Making

2017

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“…Usually, together with the solution obtained, it is convenient to know the degree of agreement reached by these experts [8,18,54,48].…”

Section: Introductionmentioning

confidence: 99%

An analysis of consensus approaches based on different concepts of coincidence

Moral

Tapia

Chiclana

et al. 2018

IFS

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Soft consensus is a relevant topic in group decision making problems. Soft consensus measures are utilized to reflect the different agreement degrees between the experts leading the consensus reaching process. This may determine the final decision and the time needed to reach it. The concept of coincidence has led to two main approaches to calculating the soft consensus measures, namely, concordance among expert preferences and concordance among individual solutions. In the first approach the coincidence is obtained by evaluating the similarity among the expert preferences, while in the second one the concordance is derived from the measurement of the similarity among the solutions proposed by these experts. This paper performs a comparative study of consensus approaches based on both coincidence approaches. We obtain significant differences between both approaches by comparing several distance functions for measuring expert preferences and a consensus measure over the set of alternatives for measuring the solutions provided by experts. To do so, we use the nonparametric Wilcoxon signed-ranks test. Finally, these outcomes are analyzed using Friedman mean ranks in order to obtain a quantitative classification of the considered measurements according to the convergence criterion considered in the consensus reaching process.

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“…Feng et al [38] proposed a consistency measure method based on the hesitant goal programming model to define the consistency hesitant fuzzy linguistic preference relations. Wu and Xu [39] proposed a large-scale group decision-making consensus model with possibility distribution based hesitant fuzzy preference. Li et al [40] personalized individual semantics in group decision-making with hesitant fuzzy linguistic terms sets by consensus model.…”

Section: Introductionmentioning

confidence: 99%

Grey Relational Analysis for Hesitant Fuzzy Sets and Its Applications to Multiattribute Decision-Making

Guan¹,

Sun²,

Xiao³

et al. 2018

Mathematical Problems in Engineering

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Due to the superiority in expressing the uncertain and vague information, the hesitant fuzzy set (HFS) is regarded as an important tool to deal with multiattribute decision-making (MADM) problems. Quantitative and qualitative fuzzy measures have been proposed to solve such problems from different points. However, most of the existing information measures for HFSs are related to such fuzzy measures as distance, similarity, entropy, and correlation coefficients. The grey relational analysis is omitted. Besides, the existing grey relational analysis for HFSs only considers the range or distance between HFSs data which is only a partial measure of the HFSs. Therefore, in this paper, we improve the grey relational analysis for HFSs and explore a novel slope grey relational degree by considering another factor of HFSs data: the slope. Further, we combine both the distance and slope factors of HFSs data to construct a synthetic grey relational degree that describes the closeness and variation tendency of HFSs simultaneously, greatly enriching the fuzzy measures of HFSs. Furthermore, with the help of the TOPSIS method, we develop the grey relational based MADM methodology to solve the HFSs MADM problems. Finally, combining with two practical MADM examples about energy policy selection and multisensor target recognition, we obtain the most desirable decision results. Compared with the previous methods, the validity, comprehensiveness, and discrimination of the proposed synthetic grey relational degree for HFSs are demonstrated in detail.

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A consensus model for large-scale group decision making with hesitant fuzzy information and changeable clusters

Cited by 334 publications

References 57 publications

Customer Purchasing Behavior Analysis as Alternatives for Supporting In-Store Green Marketing Decision-Making

Customer Purchasing Behavior Analysis as Alternatives for Supporting In-Store Green Marketing Decision-Making

An analysis of consensus approaches based on different concepts of coincidence

Grey Relational Analysis for Hesitant Fuzzy Sets and Its Applications to Multiattribute Decision-Making

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