Intuitionistic fuzzy two-sided matching model and its application to personnel-position matching problems

Yu, Dejian; Zhang, Xu

doi:10.1080/01605682.2018.1546662

Cited by 65 publications

(33 citation statements)

References 50 publications

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“…e future research work is mainly divided into two aspects: on the one hand, we will continue to promote the application of this method in related fields, such as software outsourcing service provider selection, information security assessment, and software product quality assessment, especially for the evaluation of external and internal software quality; on the other hand, we will continue to study the combination between INNs and theoretical methods, such as two-sided matching model [57], TODIM method, and the prospect theory.…”

Section: Resultsmentioning

confidence: 99%

The Projection Model with Unknown Weight Information under Interval Neutrosophic Environment and Its Application to Software Quality-in-Use Evaluation

Wang

2020

Mathematical Problems in Engineering

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Interval neutrosophic sets (INSs) provide us with a more flexible and effective way to express incomplete, indeterminate, and inconsistent information. The purpose of this paper is to introduce the new multicriteria decision-making (MCDM) method based on the improved projection model under the interval neutrosophic environment. In this paper, we investigated the basic concepts and operational rules of interval neutrosophic numbers (INNs), then proposed the projection of two INNs and improved the entropy formula of the INNs. Furthermore, this paper took account into the decision maker’s attitude towards the indeterminacy and risk and proposed two different methods to determine the ideal solutions. Based on this, we presented an improved MCDM method based on the projection model under the interval neutrosophic environment. Finally, the practicability and reliability of the proposed method were explained by the example of software quality-in-use evaluation.

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Section: Resultsmentioning

confidence: 99%

The Projection Model with Unknown Weight Information under Interval Neutrosophic Environment and Its Application to Software Quality-in-Use Evaluation

Wang

2020

Mathematical Problems in Engineering

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“…In contrast, some scholars developed another popular tool named as optimization model to help experts achieve consensus (Ben-Arieh & Easton, 2007;Fan et al, 2006;Meng et al, 2019;Wan et al, 2018;Wu et al, 2019aWu et al, , 2019bXu et al, 2018;Yu & Xu, 2020;Zhang et al, 2018aZhang & Pedrycz, 2018). As far as we know, the most important advantage of optimization models is that they can provide the adjusted preference solutions directly by setting goals and solving the established models.…”

Section: Introductionmentioning

confidence: 99%

Managing Consensus by Multi-Stage Optimization Models With Linguistic Preference Orderings and Double Hierarchy Linguistic Preferences

Gou

Zhang

Zhou

2020

Technological and Economic Development of Economy

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Preference ordering structures are useful and popular tools to represent experts’ preferences in the decision making process. In the existing preference orderings, they lack the research on the precise relationship between any two adjacent alternatives in the preference orderings, and the decision making methods are unreasonable. To overcome these issues, this paper establishes a novel concept of linguistic preference ordering (LPO) in which the ordering of alternatives and the relationships between two adjacent alternatives should be fused well, and develops two transformation models to transform each LPO into the corresponding double hierarchy linguistic preference relation with complete consistency. Additionally, to fully respect the experts’ expression habits and provide more refined solutions to experts, this paper establishes a multi-stage consensus optimization model by considering the suggested preferences represented in both the continuous scale and the discrete scale, and develops a multi-stage interactive consensus reaching algorithm to deal with multi-expert decision making problem with LPOs. Furthermore, some numerical examples are presented to illustrate the developed methods and models. Finally, some comparative analyses between the proposed methods and models and some existing methods have been made to show the advantages of the proposed methods and models.

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“…The developed new similarity measure between TrIFNs was also used to present an TsM approach [31]. The application of IVIFSs can be found in the following literature [29], [32]. A TsM model for the personnel-position matching problem is designed, which was based on several new intuitionistic fuzzy Choquet integral operators [32].…”

Section: Introductionmentioning

confidence: 99%

“…The application of IVIFSs can be found in the following literature [29], [32]. A TsM model for the personnel-position matching problem is designed, which was based on several new intuitionistic fuzzy Choquet integral operators [32]. The TsM matching problem with IvIFNs and matching aspirations was studied [29].…”

Section: Introductionmentioning

confidence: 99%

“…The TsM matching problem with IvIFNs and matching aspirations was studied [29]. But the TsM model developed in reference [32] may be only applied into the personnel-position matching problem. The interval-valued scores proposed in reference [29] may be less than zero, and the considered factors for determine matching aspirations in reference [29] may be incomplete.…”

Section: Introductionmentioning

confidence: 99%

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TOPSIS Based Two-Sided Matching Under Interval-Valued Intuitionistic Fuzzy Environment in Virtual Reality Technology Transfer

Yue

Zhang

2020

IEEE Access

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Bodies' behaviors remain important to the decision-making process of two-sided matching. The two-sided matching problem under interval-valued intuitionistic fuzzy environment is investigated from the perspective of bodies' behavior, i.e., the behavior of matching willingness. For solving the problem, a normalized interval-valued score function is firstly presented. Through using this function, interval-valued intuitionistic fuzzy number (IvIFN) preference matrices are converted to normalized interval-valued score matrices. The normalized interval-valued score matrices are then converted to score matrices. Based on score matrices, the matching willingness can be obtained by solving an optimal model. Based on score matrices and matching willingness matrix, the weighting score matrices are set up. Aiming at weighting score matrices, we use the TOPSIS method to calculate the closeness degrees. Based on closeness degree matrices and matching matrix, a two-sided matching (TsM) model is developed. Considering the same or different statuses of bodies, the TsM model is transformed to the one-goal TsM model. Through model solution, the optimal scheme of TsM can be obtained. Ultimately, the availability of TOPSIS based TsM method is illustrated by using a matching example of virtual reality technology. INDEX TERMS Two-sided matching, interval-valued intuitionistic fuzzy number, bodies' behavior, model, virtual reality technology.

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Intuitionistic fuzzy two-sided matching model and its application to personnel-position matching problems

Cited by 65 publications

References 50 publications

The Projection Model with Unknown Weight Information under Interval Neutrosophic Environment and Its Application to Software Quality-in-Use Evaluation

The Projection Model with Unknown Weight Information under Interval Neutrosophic Environment and Its Application to Software Quality-in-Use Evaluation

Managing Consensus by Multi-Stage Optimization Models With Linguistic Preference Orderings and Double Hierarchy Linguistic Preferences

TOPSIS Based Two-Sided Matching Under Interval-Valued Intuitionistic Fuzzy Environment in Virtual Reality Technology Transfer

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