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The use of belief decision matrices for MCDA problem modelling in the ER approach results in the following features:

(1) An assessment of an option can be more reliably and realistically represented by a belief decision matrix than by a conventional decision matrix.

(2) It accepts data of different formats with various types of uncertainties as inputs, such as single numerical values, probability distribution, and subjective judgments with belief degrees.

(3) It allows all available information embedded in different data formats, including qualitative and incomplete data, to be maximally incorporated in assessment and decision making processes.

(4) It allows assessment outcomes to be represented more informatively.

The ER approach is implemented in a software tool called Intelligent Decison System .


REFERENCES



FURTHER READING


  • Keeney, R.L. and Raiffa, H. (1976), Decisions with Multiple Objectives, Cambridge University Press.


  • Shafer, G.A. (1976), Mathematical Theory of Evidence, Princeton University Press.


  • J. B. Yang, “Rule and utility based evidential reasoning approach for multiple attribute decision analysis under uncertainty”, European Journal of Operational Research, Vol. 131, No.1, pp.31-61, 2001.


  • Yang, J.B. and Xu, D.L. (2002), On the evidential reasoning algorithm for multiple attribute decision analysis under uncertainty, IEEE Transactions on Systems, Man and Cybernetics Part A: Systems and Humans Vol. 32, 289-304.



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