The analytic hierarchy process with stochastic judgements
Abstract
The analytic hierarchy process (AHP) is a widely-used method for multicriteria decision support based on the hierarchical decomposition of objectives, evaluation of preferences through pairwise comparisons, and a subsequent aggregation into global evaluations. The current paper integrates the AHP with stochastic multicriteria acceptability analysis (SMAA), an inverse-preference method, to allow the pairwise comparisons to be uncertain. A simulation experiment is used to assess how the consistency of judgements and the ability of the SMAA-AHP model to discern the best alternative deteriorates as uncertainty increases. Across a range of simulated problems results indicate that, according to conventional benchmarks, judgements are likely to remain consistent unless uncertainty is severe, but that the presence of uncertainty in almost any degree is sufficient to make the choice of best alternative unclear.
Citation
Durbach , I N , Lahdelma , R & Salminen , P 2014 , ' The analytic hierarchy process with stochastic judgements ' , European Journal of Operational Research , vol. 238 , no. 2 , pp. 552-559 . https://doi.org/10.1016/j.ejor.2014.03.045
Publication
European Journal of Operational Research
Status
Peer reviewed
ISSN
0377-2217Type
Journal article
Rights
Copyright © 2014 Elsevier. All rights reserved. This work has been made available online in accordance with publisher policies or with permission. Permission for further reuse of this content should be sought from the publisher or the rights holder. This is the author created accepted manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at http://doi.org/10.1016/j.ejor.2014.03.045.
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