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A new group ranking approach for ordinal preferences based on group maximum consensus sequences

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  • Ma, Li-Ching

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.

Suggested Citation

  • Ma, Li-Ching, 2016. "A new group ranking approach for ordinal preferences based on group maximum consensus sequences," European Journal of Operational Research, Elsevier, vol. 251(1), pages 171-181.
    • Handle: RePEc:eee:ejores:v:251:y:2016:i:1:p:171-181
    DOI: 10.1016/j.ejor.2015.10.042
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    References listed on IDEAS

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    Cited by:

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    2. Li-Ching Ma, 2018. "Discovering Consensus Preferences Visually Based on Gower Plots," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 17(03), pages 741-761, May.
    3. Zhang, Huanhuan & Kou, Gang & Peng, Yi, 2019. "Soft consensus cost models for group decision making and economic interpretations," European Journal of Operational Research, Elsevier, vol. 277(3), pages 964-980.
    4. Wenjun Chang & Chao Fu & Nanping Feng & Shanlin Yang, 2021. "Multi-criteria Group Decision Making with Various Ordinal Assessments," Group Decision and Negotiation, Springer, vol. 30(6), pages 1285-1314, December.
    5. Gong, Zaiwu & Guo, Weiwei & Słowiński, Roman, 2021. "Transaction and interaction behavior-based consensus model and its application to optimal carbon emission reduction," Omega, Elsevier, vol. 104(C).
    6. Wu, Xingli & Liao, Huchang, 2019. "A consensus-based probabilistic linguistic gained and lost dominance score method," European Journal of Operational Research, Elsevier, vol. 272(3), pages 1017-1027.
    7. Min Xue & Chao Fu & Shan-Lin Yang, 2021. "Dynamic Expert Reliability Based Feedback Mechanism in Consensus Reaching Process with Distributed Preference Relations," Group Decision and Negotiation, Springer, vol. 30(2), pages 341-375, April.

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