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has been cited by the following article:

• TITLE: Uncertainty Weight Generation Approach Based on Uncertainty Comparison Matrices

  AUTHORS: Chao Wang, Liang Lin, Jiajun Liu

  KEYWORDS: AHP; Uncertainty Theory; Uncertain Variable; Uncertainty Distribution; Uncertainty Comparison Matrix; Uncertain Variable Method

  JOURNAL NAME: Applied Mathematics, Vol.3 No.5, May 16, 2012

  ABSTRACT: 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.