A two-stage consensus method for large-scale multi-attribute group decision making with an application to earthquake shelter selection
•A two-stage method to support the consensus reaching process for LSGDM problems is presented.•The first stage classifies the LSG into several sub-clusters by utilizing the SOM.•An iterative algorithm is proposed to obtain the group preference for each sub-cluster.•Comparative analysis is provided t...
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| Published in: | Computers & industrial engineering 2018-02, Vol.116, p.113-129 |
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| Main Authors: | , , |
| Format: | Article |
| Language: | eng |
| Subjects: | |
| Online Access: | Get full text |
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| Summary: | •A two-stage method to support the consensus reaching process for LSGDM problems is presented.•The first stage classifies the LSG into several sub-clusters by utilizing the SOM.•An iterative algorithm is proposed to obtain the group preference for each sub-cluster.•Comparative analysis is provided to show the advantages.
In multi-attribute group decision making, it is preferable that a set of experts reach a high degree of consensus amongst their opinions, especially for large-scale group decision making. This paper presents a two-stage method to support the consensus reaching process for large-scale multi-attribute group decision making problems. The first stage classifies the large-scale group into several sub-clusters by utilizing the self-organizing maps and, then, an iterative algorithm is proposed to obtain the group preference for each sub-cluster. The second stage treats the group preference of each sub-cluster as the representative preference and collapses each sub-cluster to form a smaller and more manageable group. Then the aforesaid iterative algorithm is utilized to process the new set and select the best alternative(s). Finally, a case study of real application to earthquake shelter selection and comparative analysis are given to verify the effectiveness of the proposed method. |
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| ISSN: | 0360-8352 1879-0550 |