DocumentCode :
344597
Title :
Multicriteria analysis with fuzzy pairwise comparison
Author :
Deng, Hepu
Author_Institution :
Fac. of Inf. Technol., Monash Univ., Churchill, Vic., Australia
Volume :
2
fYear :
1999
fDate :
22-25 Aug. 1999
Firstpage :
726
Abstract :
Presents an approach for solving qualitative multicriteria analysis (MA) problems using fuzzy pairwise comparison. Fuzzy numbers are used to approximate the decision-maker´s (DM´s) subjective assessments in assessing alternative performance and criteria importance. The concept of fuzzy extent analysis is applied for solving the reciprocal judgement matrices. To avoid the complex and unreliable process of comparing fuzzy utilities, the /spl alpha/-cut technique is applied to transform the fuzzy performance matrix into an interval matrix. Incorporated with the DM´s attitude towards risk, an overall performance index is obtained for each alternative across all criteria in line with the ideal solution concept. An empirical study of a tender selection problem in Australia is conducted. The result shows that the approach developed is simple and comprehensible in concept, efficient in computation, and robust and flexible in modeling the human evaluation process, thus making it of general use for solving practical MA problems.
Keywords :
decision theory; fuzzy set theory; matrix algebra; /spl alpha/-cut technique; Australia; decision-maker; fuzzy extent analysis; fuzzy numbers; fuzzy pairwise comparison; fuzzy performance matrix; human evaluation process; ideal solution concept; interval matrix; multicriteria analysis; performance index; reciprocal judgement matrices; subjective assessments; tender selection problem; Australia; Decision making; Delta modulation; Fuzzy sets; Humans; Information analysis; Information technology; Performance analysis; Robustness; Surface acoustic waves;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems Conference Proceedings, 1999. FUZZ-IEEE '99. 1999 IEEE International
Conference_Location :
Seoul, South Korea
ISSN :
1098-7584
Print_ISBN :
0-7803-5406-0
Type :
conf
DOI :
10.1109/FUZZY.1999.793038
Filename :
793038
Link To Document :
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