Abstract
One of the most popular methods of calculating priorities based on the pairwise comparisons matrices (PCM) is the geometric mean method (GMM). It is equivalent to the logarithmic least squares method (LLSM), so some use both names interchangeably, treating it as the same approach. The main difference, however, is in the way the calculations are done. It turns out, however, that a similar relationship holds for incomplete matrices. Based on Harker’s method for the incomplete PCM, and using the same substitution for the missing entries, it is possible to construct the geometric mean solution for the incomplete PCM, which is fully compatible with the existing LLSM for the incomplete PCM. Again, both approaches lead to the same results, but the difference is how the final solution is computed. The aim of this work is to present in a concise form, the computational method behind the geometric mean method (GMM) for an incomplete PCM. The computational method is presented to emphasize the relationship between the original GMM and the proposed solution. Hence, everyone who knows the GMM for a complete PCM should easily understand its proposed extension. Theoretical considerations are accompanied by a numerical example, allowing the reader to follow the calculations step by step.
Subject
General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)
Reference52 articles.
1. Ramon Llull: from ‘Ars electionis’ to social choice theory
2. Essay on the Application of Analysis to the Probability of Majority Decisions;Condorcet,1785
3. A law of comparative judgment.
4. A “reasonable” social welfare function;Copeland,1951
5. A scaling method for priorities in hierarchical structures
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