A question on fuzzy multiple attributes decision-making


Subject: A question on fuzzy multiple attributes decision-making
From: Keping Chen (kchen@ocs.mq.edu.au)
Date: Sun Jul 30 2000 - 22:10:36 MET DST


Dear List,

I currently involve in a risk analysis project using fuzzy-based
Multi-Criteria Evaluation (MCE). The project is to compare the composite
risk levels across a series of locations. Four input factors, namely
tropical cyclone, earthquake, hail and tornado, are considered. Given that
individual scales (e.g. low, medium, high) for the above each factor are
known, I use a simple stanardisation approach to converting these
linguistic terms to fuzzy numbers to crisp numbers ranging 0 to 1.
Individual weights, which reflect the relative importance between
factors, are also estimated. Finally I calculate a composite value for
each location with the weighted linear combination method.

For example, locations A, B, C and D have composite values of 0.3, 0.2,
0.6 and 0.5, respectively. During the ranking stage, I get the order of
risk levels, C > D > A > B (i.e. location C has the highest risk level in
this case). My question goes to how to really compare the difference
between these locations, based on the composite values. Say, the risk
level of C is as twice large as A, as three times large as B? Can I
confidently say that?

Your suggestion on this question and relevant books, articles and websites
is greatly appreciated. Look forward to your reply.

Keping Chen

 

      

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