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Hokkaido University Collection of Scholarly and Academic Papers >
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Multiple-Attribute Decision Making Under Uncertainty: The Evidential Reasoning Approach Revisited
| Title: | Multiple-Attribute Decision Making Under Uncertainty: The Evidential Reasoning Approach Revisited |
| Authors: | Huynh, Van-Nam Browse this author | | Nakamori, Yoshiteru Browse this author | | Ho, Tu-Bao Browse this author | | Murai, Tetsuya Browse this author →KAKEN DB |
| Keywords: | assessment | | evidence combination | | evidential reasoning (ER) | | multiple-attribute decision making (MADM) | | uncertainty |
| Issue Date: | Jul-2006 |
| Publisher: | IEEE |
| Journal Title: | IEEE Transactions on Systems Man and Cybernetics - Part A Systems and Humans |
| Volume: | 36 |
| Issue: | 4 |
| Start Page: | 804 |
| End Page: | 822 |
| Publisher DOI: | 10.1109/TSMCA.2005.855778 |
| Abstract: | In multiple-attribute decision making (MADM) problems, one often needs to deal with decision information with uncertainty. During the last decade, Yang and Singh (1994) have proposed and developed an evidential reasoning (ER) approach to deal with such MADM problems. Essentially, this approach is based on an evaluation analysis model and Dempster's rule of combination in the Dempster–Shafer (D–S) theory of evidence. This paper reanalyzes the ER approach explicitly in terms of D–S theory and then proposes a general scheme of attribute aggregation in MADM under uncertainty. In the spirit of such a reanalysis, previous ER algorithms are reviewed and two other aggregation schemes are discussed. Theoretically, it is shown that new aggregation schemes also satisfy the synthesis axioms, which have been recently proposed by Yang and Xu (2002) for which any rational aggregation process should grant. A numerical example traditionally examined in published sources on the ER approach is used to illustrate the discussed techniques. |
| Rights: | ©2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. |
| Type: | article |
| URI: | http://hdl.handle.net/2115/14531 |
| Appears in Collections: | 情報科学院・情報科学研究院 (Graduate School of Information Science and Technology / Faculty of Information Science and Technology) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
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Submitter: 村井 哲也
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