A Correlation-Based TOPSIS Method for Multiple Attribute Decision Making with Single-Valued Neutrosophic Information

Zeng, Shouzhen; Luo, Dandan; Zhang, Chonghui; Li, Xingsen

doi:10.1142/s0219622019500512

Cited by 49 publications

(29 citation statements)

References 45 publications

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“…Obviously, the weights of the indicators must be determined beforehand when using a nonradial model. At present, most studies that have used nonradial models have determined the set of weights based on experience [45], [46], as with the AHP method and the Delphi method [47]. However, these methods inaccurately reflect the characteristics of each decision variable, and consequently, they are not likely to be a fair evaluation.…”

Section: Nonradial Sdea Methodologymentioning

confidence: 99%

A Nonradial Super Efficiency DEA Framework Using a MCDM to Measure the Research Efficiency of Disciplines at Chinese Universities

Ding-xin

et al. 2020

IEEE Access

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Evaluating the efficiency of scientific research plays an important role in accelerating technological innovation and optimizing the allocation of research resources. Most studies have focused on measuring research efficiency from a macro perspective, ignoring differences within disciplines. Furthermore, existing methods have failed to discriminate between evaluation results and the fact that research has variable returns to scale. To address this, in this paper we propose a multiple-criteria decision-making (MCDM) nonradial super efficiency data envelopment analysis (NRSDEA) model, which uses an outputoriented nonradial SDEA method to manage nonsolution problems and integer decision variable constraints. In addition, we used a Malmquist index to decompose the productivity changes of statistics discipline's research efficiency at different universities in China. Finally, we verified the rationality and effectiveness of the proposed method. INDEX TERMS Discipline research efficiency, multiple-criteria decision-making, nonradial SDEA, Malmquist index.

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Section: Nonradial Sdea Methodologymentioning

confidence: 99%

A Nonradial Super Efficiency DEA Framework Using a MCDM to Measure the Research Efficiency of Disciplines at Chinese Universities

Ding-xin

et al. 2020

IEEE Access

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“…Inspired by Zeng et al [52] and Zhang et al [53], three different measures are proposed in this study to further expand the MCGDM method in the HPFS environment and solve the site selection problem in the ULC.…”

Section: Hesitant Probabilistic Fuzzy Number Weighted Logarithmic mentioning

confidence: 99%

A Hesitant Probabilistic Fuzzy Multi-Criteria Group Decision-Making Framework for Urban Land Consolidation in China

Zhang

et al. 2020

IEEE Access

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Urban land consolidation (ULC) is a technique used globally for urbanization planning. Selecting a suitable area for ULC becomes the most feasible plan for urban redevelopment in China, which can be regarded as a complex multi-criteria group decision-making problem. In this paper, a hesitant probabilistic fuzzy multi-criteria group decision-making framework is proposed to solve the site selection problem of ULC. In the framework, hesitant probabilistic fuzzy set are used to represent the evaluation information provided by decision makers. Furthermore, the framework utilizes a new method based on entropy and the analytic hierarchy process for determining weights. The hesitant probabilistic fuzzy combined weighted logarithmic averaging distance (HPFCWLAD) measure is then introduced for sorting the alternatives found by the system. To validate the proposed framework, a site selection case of ULC including five alternatives in Hangzhou is investigated. The effectiveness and stability of the framework is proved through a comparative analysis. INDEX TERMS Urban land consolidation; Ordered weighted distance measure; Site selection problem; Hesitant probabilistic fuzzy; Multi-criteria group decision-making

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“…The Pearson correlation coefficient is an important tool to reflect the degree of correlation between two variables or sets [19]. Up to now, the research of correlation coefficients has been extended from classic crisp numbers to several uncertain situations [20][21][22][23][24][25][26][27][28][29]. The value of a correlation coefficient generally lies in the interval [−1,1] in the statistical area.…”

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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A Correlation-Based TOPSIS Method for Multiple Attribute Decision Making with Single-Valued Neutrosophic Information

Cited by 49 publications

References 45 publications

A Nonradial Super Efficiency DEA Framework Using a MCDM to Measure the Research Efficiency of Disciplines at Chinese Universities

A Nonradial Super Efficiency DEA Framework Using a MCDM to Measure the Research Efficiency of Disciplines at Chinese Universities

A Hesitant Probabilistic Fuzzy Multi-Criteria Group Decision-Making Framework for Urban Land Consolidation in China

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

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