PROJECT TITLE :
2-Additive Capacity Identification Methods From Multicriteria Correlation Preference Information
The essential role of the particular families of capacities and also the capability identification ways is to help the choice maker to house the exponential complexity inherent in the development method of the capacity. The a pair of-additive capacities seem to be the most in style among the actual families of capacities since they allow to model interactions between criteria whereas preserving simplicity. Besides the preference with respect to the choice criteria, most of the capability identification methods additionally would like to supply the desired overall evaluations of the choice alternatives in the educational set, that is a time-consuming task for the choice maker. In this paper, we propose some models to identify a pair of-additive capacities only from a reasonably refined preference data with respect to the decision criteria known as the multicriteria correlation preference info (MCCPI). The MCCPI is a cluster of 2-D preference information that can be described and obtained by the refined diamond diagram. The common principle of the proposed models is to minimize the various sorts of deviations between the MCCPI and the foremost desired 2-additive capacity(ies). A multicriteria decision creating example is presented to point out the feasibility of the proposed strategies, and a a pair of-D scale of the MCCPI is also introduced within the further discussion of the illustrative example.
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