A new group ranking approach for ordinal preferences based on group maximum consensus sequences.
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| Title: | A new group ranking approach for ordinal preferences based on group maximum consensus sequences. |
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| Authors: | Ma, Li-Ching1 lcma@nuu.edu.tw |
| Source: | European Journal of Operational Research. May2016, Vol. 251 Issue 1, p171-181. 11p. |
| Subjects: | Problem solving, Decision making, Matrices (Mathematics), Mathematical sequences, Mathematical optimization |
| Abstract: | Group ranking problems involve aggregating individual rankings to generate group ranking which represents consolidated group preference. Group ranking problems are commonly applied in real-world decision-making problems; however, supporting a group decision-making process is difficult due to the existence of multiple decision-makers, each with his/her own opinions. Hence, determining how to best aid the group ranking process is an important consideration. This study aims to determine a total ranking list which meets group consensus preferences for group ranking problems. A new group consensus mining approach based on the concept of tournament matrices and directed graphs is first developed; an optimization model involving maximum consensus sequences is then constructed to achieve a total ranking list. Compared to previous methods, the proposed approach can generate a total ranking list involving group consensus preferences. It can also determine maximum consensus sequences without the need for tedious candidate generation processes, while also providing flexibility in solving ranking problems using different input preferences that vary in format and completeness. In addition, consensus levels are adjustable. [ABSTRACT FROM AUTHOR] |
| Copyright of European Journal of Operational Research is the property of Elsevier B.V. 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: 112676130 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: A new group ranking approach for ordinal preferences based on group maximum consensus sequences. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Ma%2C+Li-Ching%22">Ma, Li-Ching</searchLink><relatesTo>1</relatesTo><i> lcma@nuu.edu.tw</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22European+Journal+of+Operational+Research%22">European Journal of Operational Research</searchLink>. May2016, Vol. 251 Issue 1, p171-181. 11p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Problem+solving%22">Problem solving</searchLink><br /><searchLink fieldCode="DE" term="%22Decision+making%22">Decision making</searchLink><br /><searchLink fieldCode="DE" term="%22Matrices+%28Mathematics%29%22">Matrices (Mathematics)</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+sequences%22">Mathematical sequences</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+optimization%22">Mathematical optimization</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Group ranking problems involve aggregating individual rankings to generate group ranking which represents consolidated group preference. Group ranking problems are commonly applied in real-world decision-making problems; however, supporting a group decision-making process is difficult due to the existence of multiple decision-makers, each with his/her own opinions. Hence, determining how to best aid the group ranking process is an important consideration. This study aims to determine a total ranking list which meets group consensus preferences for group ranking problems. A new group consensus mining approach based on the concept of tournament matrices and directed graphs is first developed; an optimization model involving maximum consensus sequences is then constructed to achieve a total ranking list. Compared to previous methods, the proposed approach can generate a total ranking list involving group consensus preferences. It can also determine maximum consensus sequences without the need for tedious candidate generation processes, while also providing flexibility in solving ranking problems using different input preferences that vary in format and completeness. In addition, consensus levels are adjustable. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of European Journal of Operational Research is the property of Elsevier B.V. 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: 10.1016/j.ejor.2015.10.042 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 11 StartPage: 171 Subjects: – SubjectFull: Problem solving Type: general – SubjectFull: Decision making Type: general – SubjectFull: Matrices (Mathematics) Type: general – SubjectFull: Mathematical sequences Type: general – SubjectFull: Mathematical optimization Type: general Titles: – TitleFull: A new group ranking approach for ordinal preferences based on group maximum consensus sequences. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Ma, Li-Ching IsPartOfRelationships: – BibEntity: Dates: – D: 16 M: 05 Text: May2016 Type: published Y: 2016 Identifiers: – Type: issn-print Value: 03772217 Numbering: – Type: volume Value: 251 – Type: issue Value: 1 Titles: – TitleFull: European Journal of Operational Research Type: main |
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