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| Content Provider | Springer Nature Link |
|---|---|
| Author | Tong, Xin Yu, Liying |
| Copyright Year | 2015 |
| Abstract | In multiple attribute decision making (MADM), hesitant fuzzy sets (HFSs) are powerful tools for expressing uncertain and vague information. Recently, MADM problems with hesitant fuzzy information have attracted increasing attention, and many MADM methods have been developed. However, only a limited amount of research has considered MADM problems that simultaneously determine attribute weights and decision-maker (DM) preferences. Therefore, we propose an MADM approach for such problems under a hesitant fuzzy environment. First, we derive extended distance and correlation coefficient measures for HFSs that are more reasonable and effective when the DM preferences are considered. We then apply the extended distance measure to subjective and objective preference information to determine attribute weights, and use these to calculate the weighted correlation coefficient between the ideal choice and each alternative. Further, we determine the ranking order of all alternatives, from which it is easy to identify the best choice. Finally, we present an example that demonstrates the practicality of the proposed approach. |
| Starting Page | 4449 |
| Ending Page | 4461 |
| Page Count | 13 |
| File Format | |
| ISSN | 14327643 |
| Journal | Soft Computing |
| Volume Number | 20 |
| Issue Number | 11 |
| e-ISSN | 14337479 |
| Language | English |
| Publisher | Springer Berlin Heidelberg |
| Publisher Date | 2015-07-03 |
| Publisher Place | Berlin, Heidelberg |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Hesitant fuzzy information Distance measure Correlation coefficient measure Decision-maker preferences Multiple attribute decision making (MADM) Computational Intelligence Artificial Intelligence (incl. Robotics) Mathematical Logic and Foundations Control, Robotics, Mechatronics |
| Content Type | Text |
| Resource Type | Article |
| Subject | Theoretical Computer Science Software Geometry and Topology |
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