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Tytuł artykułu

Relationship between priority ratios disturbances and priority estimation errors

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Języki publikacji
EN
Abstrakty
EN
This article is devoted to some problems connected with multicriteria decision analysis. We consider the relationship between the pairwise comparison matrix (PCM) and a priority vector (PV) obtained on the basis of this matrix. The PCM elements are the decision makers’ judgments about priority ratios i.e. the ratios of weights contained in the PV. It is known, that in the case of consistent matrix, we can obtain the exact value of related PV. However, the real-world practice shows that the decision maker does not create a perfectly consistent PCM, and thus usually in such a matrix the judgment’s errors occur. In our paper we use Monte Carlo simulation to study the relationship between various possible distributions of these errors and the distributions of the errors in estimates of the true PV. In these simulation we apply some initial families distribution and some different parameters. We obtain interesting results which show very slight influence families distribution on final PV errors. Our paper show that much bigger influence on simulation result have adopted parameters than selection distribution family.
Rocznik
Strony
143--154
Opis fizyczny
Bibliogr. 23 poz., rys., tab.
Twórcy
  • Institute of Mathematics, Czestochowa University of Technology Częstochowa, Poland
Bibliografia
  • [1] Saaty T.L., Decision making - the analytic hierarchy and network processes (Ahp/Anp), Journal of Systems Science and Systems Engineering 2004, 13, 1.
  • [2] Saaty T.L., The Analytic Hierarchy Process, McGraw Hill, New York 1980.
  • [3] Saaty T.L., Decision making with the AHP: Why is the principal eigenvector necessary, European Journal of Operational Research, 145, 85-91, 2003.
  • [4] Sun L., Greenberg B.S., Multiple group decision making: optimal priority synthesis from pairwise comparisons, Journal of Optimization Theory and Applications 2006, 130(2), 317-338.
  • [5] Ishizaka A., Labib A., Review of the main developments in the analytic hierarchy process, Expert Systems with Applications 2011, 38(11), 14336-14345.
  • [6] Grzybowski A.Z., Note on a new optimization based approach for estimating priority weights and related consistency index, Expert Systems with Applications 2012, 39, 11699-11708.
  • [7] Bryson N., A goal programming method for generating priority vectors, Journal of the Operational Research Society 1995, 46, 641-648.
  • [8] Grzybowski A.Z., New results on inconsistency indices and their relationship with the quality of priority vector estimation, Expert Systems with Applications 2016, 43, 197-212.
  • [9] Kazibudzki P.T., An examination of performance relations among selected consistency measures for simulated pairwise judgments, Annals of Operations Research 2016, 236/2, 1-20.
  • [10] Lin C.-C., An enhanced goal programming method for generating priority vectors, Journal of the Operational Research Society 2006, 57, 1491-1496.
  • [11] Choo E.U., Wedley W.C., A common framework for deriving preference values from pairwise comparison matrices, Computer & Operations Research 2004, 31, 893-908.
  • [12] Basak I., Comparison of statistical procedures in analytic hierarchy process using a ranking test, Mathematical and Computer Modelling 1998, 28, 105-118.
  • [13] Wrzalik A., Niedbał R., Sokołowski A., The model of managerial decisions’ support in the process of choosing an internet shop application, Polish Journal of Management Studies 2015, 12(2), 2081-7452.
  • [14] Kazibudzki P.T., Redefinition of triad's inconsistency and its impact on the consistency measurement of pairwise comparison matrix, Journal of Applied Mathematics and Computational Mechanics 2016, 15(1), 71-78, DOI:10.17512/jamcm.2016.1.07.
  • [15] Brunelli M., Fedrizzi M., Axiomatic properties of inconsistency indices for pairwise comparisons, Journal of the Operational Research Society, Published online 04 December 2013.
  • [16] Altuzarra A., Moreno-Jiménez J.M., Salvador M., Consensus building in AHP-group decision making: A Bayesian approach, Operations Research 2010, 1755-1773.
  • [17] Budescu D.V., Zwick R., Rapoport A., Comparison of the analytic hierarchy process and the geometric mean procedure for ratio scaling, Applied Psychological Measurement 1986, 10, 69-78.
  • [18] Zahedi F., A simulation study of estimation methods in the analytic hierarchy process, Socio-Economic Planning Sciences 1986, 20, 347-354.
  • [19] Lin C.-C., A revised framework for deriving preference values from pairwaise comparison matrices, Europpean Journal of Operational Research 2007, 176, 1145-1150.
  • [20] Dijkstra T.K., On the extraction of weights from pairwaise comparison matrices, Central European Journal of Operations Research 2013, 21, 103-123.
  • [21] Crawford G., Williams C.A., A note on the analysis of subjective judgment matrices, Journal of Mathematical Psychology 1985, 29, 387-405.
  • [22] Cook W.D., Kress M., Deriving weights from pairwise comparison ratio matrices: An axiomatic approach, European Journal of Operational Research 1988, 37, 355-362.
  • [23] Saaty T.L., Hu G., Ranking by eigenvector versus other methods in the Analytic Hierarchy Process, Applied Mathematical Letters 1998, 11(4), 121-125.
Uwagi
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-101680d6-cb8a-4395-8b67-b42585d3fbe4
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