A Generalized Approach to Fuzzy Multi-attribute Decision Making
نویسندگان
چکیده
We propose a generalized approach to the already existing crisp methods to solve the fuzzy multiattribute decision making problem. Specifically we deal with four methods, namely Simple Additive Weighting, Linear Assignment, TOPSIS and ELECTRE, where fuzzy numbers are used to represent the ratings of the alternatives and relative weights of the attributes. Through the use of fuzzy mathematics we adapt the crisp algorithms to handle fuzzy data. This enables us to analyze fuzzy data without having to learn new algorithms. We illustrate the use of two methods due to Lee and Li & Dubois and Prade for comparison of fuzzy numbers through a numerical example.
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