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- W2574885464 abstract "Pairwise comparison matrices, a method for preference modelling and quantification in multi-attribute decision making and ranking problems, are naturally extended to the incomplete case, offering a wider range of applicability. The weighting problem is to find a weight vector that reflects the decision maker's preferences as well as possible. The logarithmic least squares problem has a unique and simply computable solution. The spanning tree approach does not assume any metric in advance, instead it goes through all minimal sufficient subsets (spanning trees) of the set of pairwise comparisons, then the weight vectors are aggregated. It is shown that the geometric mean of weight vectors, calculated from all spanning trees, is the optimal solution of the well known logarithmic least squares problem, not only for complete, as it was recently proved by Lundy, Siraj and Greco, but for incomplete pairwise comparison matrices as well." @default.
- W2574885464 created "2017-01-26" @default.
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- W2574885464 date "2017-01-16" @default.
- W2574885464 modified "2023-09-27" @default.
- W2574885464 title "The logarithmic least squares optimality of the geometric mean of weight vectors calculated from all spanning trees for (in)complete pairwise comparison matrices" @default.
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