Uncertainty Weight Generation Approach Based on Uncertainty Comparison Matrices

DOI: 10.4236/am.2012.35075   PDF   HTML     4,182 Downloads   6,881 Views   Citations


In practical application of AHP, non-deterministic factors are frequently encountered. This paper employs uncertainty theory to deal with non-deterministic factors in problems of ranking alternatives. The concepts of uncertainty comparison matrix and uncertainty weights are proposed in this paper. It also gives the uncertain variable method to calculate uncertainty weights from uncertainty comparison matrices, which can be either consistent or inconsistent. The proposed uncertain variable method (UVM) is also applicable to interval comparison matrices and fuzzy comparison ma-trices when they are transformed into uncertainty comparison matrices using linear uncertainty distribution or zigzag uncertainty distribution. The proposed approach is computationally efficient as it consists of solving only inverse uncertainty distribution. At the end of this paper, five numerical examples are given to illustrate the method.

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C. Wang, L. Lin and J. Liu, "Uncertainty Weight Generation Approach Based on Uncertainty Comparison Matrices," Applied Mathematics, Vol. 3 No. 5, 2012, pp. 499-507. doi: 10.4236/am.2012.35075.

Conflicts of Interest

The authors declare no conflicts of interest.


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