An Interval Linguistic Distribution Model for Multiple Attribute Decision Making Problems with Incomplete Linguistic Information

Wen-Tao Guo, Huynh Van-Nam and Yoshiteru Nakamori
Additional contact information
Wen-Tao Guo: School of Knowledge Science, Japan Advanced Institute of Science and Technology (JAIST), Nomi, Japan
Huynh Van-Nam: School of Knowledge Science, Japan Advanced Institute of Science and Technology (JAIST), Nomi, Japan
Yoshiteru Nakamori: School of Knowledge Science, Japan Advanced Institute of Science and Technology (JAIST), Nomi, Japan

International Journal of Knowledge and Systems Science (IJKSS), 2015, vol. 6, issue 4, 16-34

Abstract: In this paper, the authors propose an interval linguistic distribution model for multiple attribute decision making (MADM) problems with incomplete linguistic information, in which they use intervals as evaluators' confidence levels indicating their belief degrees that a linguistic term fits an evaluation. By introducing the extent of ignoring information into this model, it can deal with incomplete linguistic assessments and then allow evaluators to avoid the dilemma that they have to supply complete assessments when not available. In addition, the uncertain subjective judgments on attributes of alternatives are represented as distributions on the linguistic term set used as an instrument for assessment in this model. This feature can be regarded as a measure for evaluators to handle uncertain information. The aggregation operators and expected utilities are also introduced for the purpose of aggregation and ranking problems of interval linguistic distributions. Finally, an example is used to illuminate the proposed model.

Date: 2015
References: Add references at CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 018/IJKSS.2015100102 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jkss00:v:6:y:2015:i:4:p:16-34

Access Statistics for this article

International Journal of Knowledge and Systems Science (IJKSS) is currently edited by Van Nam Huynh

More articles in International Journal of Knowledge and Systems Science (IJKSS) from IGI Global
Bibliographic data for series maintained by Journal Editor ().