Name
Abstract | ||
|---|---|---|
This paper investigates the problem of measuring consensus in multi-perspective Multi-Criteria Group Decision Making (MCGDM) problems, in which participants have individual views on the relative importance of different evaluation criteria. A novel dual consensus measure for multi-perspective MCGDM problems is introduced. The proposed measure determines the level of agreement between participants' opinions based on: (i) the global performance or satisfaction of alternatives, (ii) their partial performances of alternatives under each criterion, and (iii) the similarity between the perspectives of participants regarding criteria weights. Preliminary experiments are conducted for an example multi-perspective MCGDM scenario. The degree to which global and partial performance information are jointly taken into account - together with the actual pairwise distances between the opinions of participants - are shown to directly affect the overall measurement of consensus in the group. An application example is introduced in a MCGDM problem on selecting the safest logistic route to transport hazardous materials. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/SMC.2018.00561 | 2018 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC) |
Field | DocType | ISSN |
Pairwise comparison,Computer science,Artificial intelligence,Machine learning,Group decision-making | Conference | 1062-922X |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ivan Palomares | 1 | 199 | 11.40 |
| Michael Crosscombe | 2 | 4 | 2.60 |
| Zhensong Chen | 3 | 57 | 8.39 |
| Jonathan Lawry | 4 | 0 | 1.01 |