An update on combinatorial method for aggregation of expert judgments in AHP
Bozóki, S., & Tsyganok, V. (2019). The (logarithmic) least squares optimality of the arithmetic (geo-metric) mean of weight vectors calculated from all spanning trees for incomplete additive (multiplicative) pairwise comparison matrices.
Brunelli, M., & Fedrizzi, M. (2011). Characterizing properties for inconsistency indices in AHP. In
Cayley, A. (1889). A theorem on trees.
Choo, E. U., & Wedley, W. C. (2004). A common framework for deriving priority vectors from pairwise comparison matrices.
Ferrari Neto, G., Lapasini Leal, G. C., Cardoza Galdamez, E. V., & de Souza, R. C. T. (2020). Prioritization of occupational health and safety indicators using the Fuzzy-AHP method.
Forman, E., & Peniwati, K. (1998). Aggregating individual judgments and priorities with the analytic hierarchy process.
Hartley, R. (1928). Transmission of information.
Holland, J. (1975).
Iida, Y. (2009). Ordinality consistency test about items and notation of a pairwise comparison matrix in AHP. In
Kadenko, S., & Tsyganok, V. (2020). An update on combinatorial method for aggregation of expert judgments in AHP. In
Kułakowski, K. (2020). On the geometric mean method for incomplete pairwise comparisons.
Lipovetsky, S. (2021). AHP in nonlinear scaling: from two-envelope problem to modeling by predictors.
Lundy, M., Siraj, S., & Greco, S. (2017). The mathematical equivalence of the “spanning tree” and row geometric mean preference vectors and its implications for preference analysis.
Mikhailov, L., & Siraj, S. (2011). Improving the ordinal consistency of pairwise comparison matrices. In
Olenko, A., & Tsyganok, V. (2016). Double entropy inter-rater agreement indices.
Oliveira Ramos, M., Silva, E. M., & Lima-Júnior, F. R. (2020). A fuzzy AHP approach to select suppliers in the Brazilian food supply chain.
Prüfer, H. (1918). Neuer Beweis eines Satzes über Permutationen.
Saaty, T. (1980).
Saaty, T. (1996).
Saaty, T. L., & Peniwati, K. (2007).
Siraj, S., Mikhailov, L., & Keane, J. (2012). Enumerating all spanning trees for pairwise comparisons.
Szádoczki, Zs., Bozóki, S., & Tekile, A. H. (2020). Proposals for the set of pairwise comparisons. In
Totsenko, V. G. (1996). The agreement degree of estimations set with regard for experts’ competence. In
Tsyganok, V. (2000). Combinatorial method of pair-wise comparisons with feedback (in Ukrainian). Data Recording.
Tsyganok, V. (2010). Investigation of the aggregation effectiveness of expert estimates obtained by the pairwise comparison method.
Tsyganok, V. V., Kadenko, S. V., & Andriichuk, O. V. (2011). Simulation of expert judgements for testing the methods of information processing in decision-making support systems.
Tsyganok, V. V., Kadenko, S. V., & Andriichuk, O. V. (2015). Using different pair-wise comparison scales for developing industrial strategies.
Tsyganok, V., Kadenko, S., & Andriychuk, O. (2020). Hybrid decision support methodology based on objective and expert data. In
Tsyganok, V., Kadenko, S., Andriichuk, O., & Roik, P. (2018). Combinatorial method for aggregation of incomplete group judgments. In
Tsyganok, V., Kadenko, S., Andriychuk, O., & Roik, P. (2017). Usage of multicriteria decision‐making support arsenal for strategic planning in environmental protection sphere.
Wollmann, D., Steiner, M. T. A., Vieira, G. E., & Steiner, P. A. (2014). Details of the analytic hierarchy process technique for the evaluation of health insurance companies.
Wu, B. Y., & Chao, K.-M. (2004).