A similarity-based approach to ranking multicriteria alternatives

Deng, H 2007, 'A similarity-based approach to ranking multicriteria alternatives' in D. Huang, L. Heutte and M. Loog (ed.) Lecture Notes in Artificial Intelligence, Springer, Berlin, Germany, pp. 253-262.


Document type: Book Chapter
Collection: Book Chapters

Title A similarity-based approach to ranking multicriteria alternatives
Author(s) Deng, H
Year 2007
Title of book Lecture Notes in Artificial Intelligence
Publisher Springer
Place of publication Berlin, Germany
Editor(s) D. Huang
L. Heutte
M. Loog
Start page 253
End page 262
Subjects Expert Systems
Decision Support and Group Support Systems
Summary This paper presents a similarity-based approach to ranking multicriteria alternatives for solving discrete multicriteria problems. The approach effectively makes use of the ideal solution concept in such a way that the most preferred alternative should have the highest degree of similarity to the positive ideal solution and the lowest degree of similarity to the negative-ideal solution. The overall performance index of each alternative across all criteria is determined based on the concept of the degree of similarity between each alternative and the ideal solution using alternative gradient and magnitude. An example is presented to demonstrate the applicability of the proposed approach. A comparative analysis between the proposed approach and the technique for order preference by similarity to ideal solution is conducted for demonstrating the merits of the proposed approach for solving discrete multicriteria analysis problems.
Copyright notice © 2007 Springer-Verlag Berlin Heidelberg
Keyword(s) multicriteria analysis
discrete optimisation
decision making
ISBN 9783540742012
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