Pairwise Comparison Matrices and their Fuzzy Extension

Development of a technology of structuring group expert judgments under various types of uncertainty

“…The matrix C, in accordance with(10), is consistent. To find the vector of local priorities, we use the linear programming method GPM[15]:w 1 =[0.354, 0.552]; w 2 =[0.170, 0.248]; w 3 =[0.083, 0.168]; w 4 =[0.159, 0.230].The expert E 2 , evaluating the significance of one alternative in relation to another triangular fuzzy number…”

“…The basis of analysing matrix (1) is the procedure for finding the priority vectors, which, provided that a ij is expressed by crisp expert evaluation, is realized by the scheme of determining the geometric mean [10]. Such an estimate is most characteristic of the scale of relations […”

“…where CI=(λ max -m)/(m-1) is the consistency index; m is the number of items to be compared; λ max is the maximum actual number of the matrix of pairwise comparisons; RI is the random index [10]. The calculated eigenvector from the matrix of paired comparisons is acceptable in the case if CR≤0.…”

“…The calculated eigenvector from the matrix of paired comparisons is acceptable in the case if CR≤0. 10.…”

“…b ij are the positive integers formed within the verbal scale[10]: the same significance is 1, the weak significance is 3, and so on, the absolute significance is 9; 2, 4, 6, and 8 are intermediate values of degrees of preference between each gradation.To find the vector of local priorities, we use the geometric mean method[10]:…”