A novel extension to VIKOR method under intuitionistic fuzzy context for solving personnel selection problem.
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| Title: | A novel extension to VIKOR method under intuitionistic fuzzy context for solving personnel selection problem. |
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| Authors: | Krishankumar, R.1 (AUTHOR), Premaladha, J.1 (AUTHOR), Ravichandran, K. S.1 (AUTHOR) ravichandran20962@gmail.com, Sekar, K. R.1 (AUTHOR), Manikandan, R.1 (AUTHOR), Gao, X. Z.2 (AUTHOR) |
| Source: | Soft Computing - A Fusion of Foundations, Methodologies & Applications. Jan2020, Vol. 24 Issue 2, p1063-1081. 19p. |
| Subjects: | Employee selection, Human capital, Multiple criteria decision making, Fuzzy sets |
| Abstract: | Personnel selection is a challenging problem for any organization. The success of a project is determined by the human resources that handle the project. To make better personnel selections, researchers have adopted multi-criteria decision-making (MCDM) approaches. Among these, fuzzy-based MCDM methods are most frequently used, as they handle vagueness and imprecision better. Intuitionistic fuzzy set (IFS) is a popular MCDM context which provides degree of membership and non-membership for preference elicitation. In this work, we propose a novel decision-making framework that consists of two stages. In the first stage, a new extension to the popular VIKOR method is presented under IFS context. The positive and negative ideal solutions are determined, and VIKOR parameters are calculated using transformation procedure. The proposed method combines the strength of both interval-valued fuzzy set and IFS that is more effective in handling vagueness with a simple formulation setup. In the second stage, a personnel selection problem is used to validate the proposed framework. Finally, the superiority and weakness of the proposed framework are discussed by comparison with other methods. [ABSTRACT FROM AUTHOR] |
| Copyright of Soft Computing - A Fusion of Foundations, Methodologies & Applications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 141100805 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: A novel extension to VIKOR method under intuitionistic fuzzy context for solving personnel selection problem. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Krishankumar%2C+R%2E%22">Krishankumar, R.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Premaladha%2C+J%2E%22">Premaladha, J.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ravichandran%2C+K%2E+S%2E%22">Ravichandran, K. S.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> ravichandran20962@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Sekar%2C+K%2E+R%2E%22">Sekar, K. R.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Manikandan%2C+R%2E%22">Manikandan, R.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Gao%2C+X%2E+Z%2E%22">Gao, X. Z.</searchLink><relatesTo>2</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Soft+Computing+-+A+Fusion+of+Foundations%2C+Methodologies+%26+Applications%22">Soft Computing - A Fusion of Foundations, Methodologies & Applications</searchLink>. Jan2020, Vol. 24 Issue 2, p1063-1081. 19p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Employee+selection%22">Employee selection</searchLink><br /><searchLink fieldCode="DE" term="%22Human+capital%22">Human capital</searchLink><br /><searchLink fieldCode="DE" term="%22Multiple+criteria+decision+making%22">Multiple criteria decision making</searchLink><br /><searchLink fieldCode="DE" term="%22Fuzzy+sets%22">Fuzzy sets</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Personnel selection is a challenging problem for any organization. The success of a project is determined by the human resources that handle the project. To make better personnel selections, researchers have adopted multi-criteria decision-making (MCDM) approaches. Among these, fuzzy-based MCDM methods are most frequently used, as they handle vagueness and imprecision better. Intuitionistic fuzzy set (IFS) is a popular MCDM context which provides degree of membership and non-membership for preference elicitation. In this work, we propose a novel decision-making framework that consists of two stages. In the first stage, a new extension to the popular VIKOR method is presented under IFS context. The positive and negative ideal solutions are determined, and VIKOR parameters are calculated using transformation procedure. The proposed method combines the strength of both interval-valued fuzzy set and IFS that is more effective in handling vagueness with a simple formulation setup. In the second stage, a personnel selection problem is used to validate the proposed framework. Finally, the superiority and weakness of the proposed framework are discussed by comparison with other methods. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Soft Computing - A Fusion of Foundations, Methodologies & Applications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s00500-019-03943-2 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 19 StartPage: 1063 Subjects: – SubjectFull: Employee selection Type: general – SubjectFull: Human capital Type: general – SubjectFull: Multiple criteria decision making Type: general – SubjectFull: Fuzzy sets Type: general Titles: – TitleFull: A novel extension to VIKOR method under intuitionistic fuzzy context for solving personnel selection problem. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Krishankumar, R. – PersonEntity: Name: NameFull: Premaladha, J. – PersonEntity: Name: NameFull: Ravichandran, K. S. – PersonEntity: Name: NameFull: Sekar, K. R. – PersonEntity: Name: NameFull: Manikandan, R. – PersonEntity: Name: NameFull: Gao, X. Z. IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 01 Text: Jan2020 Type: published Y: 2020 Identifiers: – Type: issn-print Value: 14327643 Numbering: – Type: volume Value: 24 – Type: issue Value: 2 Titles: – TitleFull: Soft Computing - A Fusion of Foundations, Methodologies & Applications Type: main |
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