This paper suggests ranking alternatives under fuzzy

\r\nMCDM (multiple criteria decision making) via an centroid based

\r\nranking approach, where criteria are classified to benefit qualitative,

\r\nbenefit quantitative and cost quantitative ones. The ratings of

\r\nalternatives versus qualitative criteria and the importance weights of

\r\nall criteria are assessed in linguistic values represented by fuzzy

\r\nnumbers. The membership function for the final fuzzy evaluation

\r\nvalue of each alternative can be developed through α-cuts and

\r\ninterval arithmetic of fuzzy numbers. The distance between the

\r\noriginal point and the relative centroid is applied to defuzzify the

\r\nfinal fuzzy evaluation values in order to rank alternatives. Finally a

\r\nnumerical example demonstrates the computation procedure of the

\r\nproposed model.<\/p>\r\n","references":"

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