Distance‐based multicriteria group decision‐making approach with probabilistic linguistic term sets

Wang, Xiaokang; Wang, Jianqiang; Zhang, Hongyu

doi:10.1111/exsy.12352

Cited by 75 publications

(42 citation statements)

References 45 publications

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“…In the future, we will take the SVNWDBM and SVNWDGBM operator in other ways such as gene selection (Huang & Liang, ). In addition, we will also take Dombi BM into diverse fuzzy environment (Alcantud & Mathew, ; Hayat, Ali, Cao, Karaaslan, & Yang, ; Peng & Wang, ; Peng & Dai, a,b; Peng, Dai, & Garg, ; Peng & Garg, ; Peng & Liu, ; Peng & Selvachandran, ; Peng & Yang, , ; Peng, Yuan, & Yang, ; Wang, Wang, & Zhang, ; Zhan & Alcantud, ; Zhang, Park, & Wu, ).…”

Section: Resultsmentioning

confidence: 99%

Novel neutrosophic Dombi Bonferroni mean operators with mobile cloud computing industry evaluation

Peng

Smarandache

2019

Expert Systems

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In the age of mobile cloud computing, we are confronted by mobility, diversity of network access types, frequent network disconnection and poor reliability, and security with complex structures. Mobile cloud computing industry decision making is crucially important for countries or societies to enhance the effectiveness and validity of leadership, which can greatly expedite industrialized and large‐scale development. In the case of mobile cloud computing industry decision evaluation, the indispensable issue arises serious inexactness, fuzziness, and ambiguity. Single‐valued neutrosophic set, disposing the indeterminacy portrayed by truth membership T, indeterminacy membership I, and falsity membership F, is a more viable and effective means to seize indeterminacy. The main purpose of the current paper is to investigate the novel operations on single‐valued neutrosophic number (SVNN) based on Dombi Bonferroni mean (DBM) and Dombi geometric Bonferroni mean (DGBM) operator, which have the enormous advantage of high flexibility with adjustable parameters. Moreover, we employ the DBM operator to present single‐valued neutrosophic DBM (SVNDBM) operator, single‐valued neutrosophic weighted DBM (SVNWDBM) operator, single‐valued neutrosophic DGBM (SVNDGBM), operator and single‐valued neutrosophic weighted DGBM (SVNWDGBM) operator for disposing with the aggregation of SVNNs and develop two multiple attribute decision making methods based on SVNWDBM and SVNWDGBM. The validity of algorithms are illustrated by a mobile cloud computing industry decision making issue, along with the sensitivity analysis of diverse parameters on the ranking. Finally, a comparison of the developed with the existing single‐valued neutrosophic decision making methods has been executed for displaying their effectiveness.

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Section: Resultsmentioning

confidence: 99%

Novel neutrosophic Dombi Bonferroni mean operators with mobile cloud computing industry evaluation

Peng

Smarandache

2019

Expert Systems

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“…In terms of the PLTS theoretical basis construction, many researchers discussed the aspects of relevant algorithms [1,2], distance and similarity measures [3,4], possibility degree measures [5,6], and information entropy measures [7]. Many scholars also extended some classic decision-making methods to PLTS situations, and explored their usefulness in decision making areas [1,[8][9][10][11][12][13][14][15]. Several scholars have successfully explored the application of the technique for order of preference by similarity to ideal solution (TOPSIS) in the PLTS environment [1,[16][17][18].…”

Section: Introductionmentioning

confidence: 99%

A Probabilistic Linguistic Multiple Attribute Decision Making Based on a New Correlation Coefficient Method and its Application in Hospital Assessment

Luo

Zeng

2020

Mathematics

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The probabilistic linguistic term set (PLTS) is a newly emerging mathematical tool for handling uncertainties. It is considered a useful extension of linguistic term sets associated with probability information and can improve the effectiveness of multiple attribute decision making (MADM). This paper proposes a new PLTS correlation coefficient and addresses its usefulness in MADM problems. For achieving this aim, some new concepts of mean, variance, and covariance of the PLTS are first proposed. Moreover, a novel PLTS Pearson correlation coefficient is defined to overcome the shortcomings of the existing methods, whose significant feature is that it lies in the interval [−1,1], which makes it more effective in reflecting the negative and positive correlation between PLTSs. A weighted PLTS Pearson correlation coefficient is further defined to consider the importance of attribute weights and expand the scope of application. Then, a relative PLTS closeness coefficient is constructed based on the developed Pearson correlation coefficient, and based on which, a Pearson correlation-based TOPSIS (technique for order of preference by similarity to ideal solution) approach for MADM problems is developed. Finally, the effectiveness as well as the applicability of the developed method are illustrated through numerical examples and comparative analysis.

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“…The evaluation information provided by DMs is inaccurate under a complex decision‐making environment. Thus, this information is provided in the form of intuitionistic fuzzy sets (IFS) (Garg & Kumar, ), Z numbers (Peng & Wang, ), probabilistic linguistic term sets (Luo, Zhang, Wang, & Li, ; Wang, Wang, & Zhang, ), and so on. Amongst them, the hesitant fuzzy set (HFS) has been applied to solve MCGDM problems (Xu & Zhou, ) because the HFS can contain more uncertain information than other fuzzy sets (Ding, Xu, & Zhao, ).…”

Section: Introductionmentioning

confidence: 99%

Multi‐criteria group decision‐making method based on TODIM with probabilistic interval‐valued hesitant fuzzy information

Zhang

Wang

2019

Expert Systems

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Probabilistic interval‐valued hesitant fuzzy sets (PIV‐HFSs) are suitable for aggregating information from different groups because the probabilistic information of all the groups can be included by using interval values. Moreover, decision makers (DMs) prefer to use interval values to provide evaluation information. Furthermore, the traditional multi‐criteria group decision‐making (MCGDM) approach has some limitations, such as obtaining the DMs' weights with inappropriate methods and neglecting the interactions amongst the criteria and the psychological characteristics of DMs. Motivated by these research background, the main contents of this study are as follows. First, PIV‐HFSs are proposed, and the convex combination operation is extended into PIV‐HFSs. Second, a hybrid MCGDM approach with PIV‐HFSs is suggested that is based on the maximizing deviation method, fuzzy analytic network process (FANP) and TODIM (an acronym in Portuguese for interactive and multi‐criteria decision‐making model). Third, an evaluation case of health management centres based on the service‐specific failure mode and effect analysis (FMEA) is considered. The results show that the most crucial secondary factor is frequency (0.35775) and that the most serious failure mode is the inaccurate check‐in. The results demonstrate that the proposed model can evaluate service quality effectively and that it performs better than other methods.

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Distance‐based multicriteria group decision‐making approach with probabilistic linguistic term sets

Cited by 75 publications

References 45 publications

Novel neutrosophic Dombi Bonferroni mean operators with mobile cloud computing industry evaluation

Novel neutrosophic Dombi Bonferroni mean operators with mobile cloud computing industry evaluation

A Probabilistic Linguistic Multiple Attribute Decision Making Based on a New Correlation Coefficient Method and its Application in Hospital Assessment

Multi‐criteria group decision‐making method based on TODIM with probabilistic interval‐valued hesitant fuzzy information

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