Bozóki, Sándor (MTA SZTAKI)

Weighting and ranking based on pairwise comparisons

Pairwise comparisons form a basis of preference modeling and decision analysis with a wide range of applications in multiple criteria decision making, group decision making, ranking and voting.

A specific model of pairwise comparisons, proposed by Saaty in 1977, is discussed in the talk. A pairwise comparison matrix is built up from numerical answers on questions like ‘How many times criterion i is more important than criterion j?’ or ‘How many times action i is better than action j?’. The problem of weighting is then to find a vector such that the pairwise ratios of its coordinates are as close as possible to the corresponding matrix elements. The eigenvector, the least squares and the logarithmic least squares methods are classical ways of weighting, besides dozens of other proposals.

Incomplete pairwise comparison matrices offer the possibility of ignoring some (in certain applications more than 90%) of all the possible pairs in the questionnaire. Due to this reduction, essentially larger weighting and ranking problems can be considered and solved. For example, we recently developed a ranking method of top tennis players.

The Pareto optimality of a weight vector, derived from a pairwise comparison matrix, is a natural and desirable property. A weight vector is called Pareto optimal if no other weight vector is at least as good in approximating the elements of the pairwise comparison matrix, and strictly better in at least one position. The least squares method and the logarithmic least squares method always yield efficient weight vectors, while the principal right eigenvector can be inefficient. It is still open to find a necessary and sufficient condition for the Pareto optimality of the eigenvector.

Main references

Bozóki, S., Fülöp, J. (2017): Efficient weight vectors from pairwise comparison matrices, European Journal of Operational Research, online first, DOI 10.1016/j.ejor.2017.06.033

Bozóki, S., Csató, L., Temesi, J. (2016): An application of incomplete pairwise comparison matrices for ranking top tennis players, European Journal of Operational Research, 248(1), 211–218, with an online appendix at http://www.sztaki.hu/%7Ebozoki/tennis/appendix.pdf

Bozóki, S., Fülöp, J., Rónyai, L. (2010): On optimal completions of incomplete pairwise comparison matrices, Mathematical and Computer Modelling, 52(1-2), 318–333

 

The talk is held in Hungarian!

Az előadás magyar nyelven lesz megtartva!

Date: Oct 31, Tuesday 4:15pm

Place: BME, Building „Q”, Room QBF13

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