Enhancement of TOPSIS using compound linguistic ordinal scale and cognitive pairwise comparison

TOPSIS is one of the popular multi-criteria decision making models. However, the determinations of the parametric settings of the rating scale and the weights for the decision matrix are still uncertain in TOPSIS. This research proposes the compound linguistic ordinal scale (CLOS) as the rating scal...

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Bibliographic Details
Published in2009 IEEE International Conference on Fuzzy Systems pp. 649 - 654
Main Author Yuen, K.K.F.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2009
Subjects
cognitive pairwise comparison
Cognitive robotics
compound linguistic variable
compound rating scale
Decision making
Distributed computing
Gaussian distribution
Large-scale systems
Multi-criteria decision making
Usability
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Summary:TOPSIS is one of the popular multi-criteria decision making models. However, the determinations of the parametric settings of the rating scale and the weights for the decision matrix are still uncertain in TOPSIS. This research proposes the compound linguistic ordinal scale (CLOS) as the rating scale for the subject measure, and the cognitive pairwise comparison (CPC) for determining the weight. The usability and applicability of the enhanced TOPSIS are illustrated in a case of the robot selection problem.
ISBN:9781424435968
142443596X
ISSN:1098-7584
DOI:10.1109/FUZZY.2009.5277319