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An application of Yager's bag theory in multicriteria based decision making problems
Author(s) -
Biswas Ranjit
Publication year - 1999
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/(sici)1098-111x(199912)14:12<1231::aid-int4>3.0.co;2-6
Subject(s) - measure (data warehouse) , fuzzy logic , similarity (geometry) , action (physics) , basis (linear algebra) , computer science , similarity measure , mathematics , artificial intelligence , data mining , machine learning , physics , geometry , quantum mechanics , image (mathematics)
We consider a problem of selecting most suitable action out of n alternatives on the basis of k factors or criteria where m judges supply information on all of these k factors/criteria. Our observation is that in many situations the criteria values are not crisp, but rather fuzzy bags. The method is based on the concept of a measure of similarity between two fuzzy bags, which is defined in this paper. An algorithm for the method is presented, and a hypothetical application‐oriented example is demonstrated. ©1999 John Wiley & Sons, Inc.