Clustering alternatives and learning preferences based on decision attitudes and weighted overlap dominance

Research output: Chapter in Book/Report/Conference proceedingBook chapterResearchpeer-review

An initial assessment on a given set of alternatives is necessary for understanding complex decision problems and their possible solutions. Attitudes and preferences articulate and come together under a decision process that should be explicitly modeled for understanding and solving the inherent conflict of decision making. This paper revises multi-criteria modeling of imprecise data, inferring outranking and indifference binary relations and classifying alternatives according to their similarity or dependency. After the initial assessment on the set of alternatives, preference orders are built according to the attitudes of decision makers, aiding the decision process by identifying solutions with minimal dissention.
Original languageEnglish
Title of host publicationFuzzy sets, rough sets, multisets and clustering
EditorsVicenç Torra, Anders Dahlbom, Yasuo Narukawa
Number of pages11
PublisherSpringer
Publication date2017
Pages337-347
ISBN (Print)978-3-319-47556-1
ISBN (Electronic)978-3-319-47557-8
DOIs
Publication statusPublished - 2017
SeriesStudies in Computational Intelligence
Volume671
ISSN1860-949X

ID: 174208465