Globally Effective Questioning in the Analytic Hierarchy Process. Millet, I. & Harker, P. T. European Journal of Operational Research, 48(1):88–97, September, 1990.
doi  abstract   bibtex   
A drawback in the use of the Analytic Hierarchy Process (AHP) is the effort required to complete all pairwise comparisons in large hierarchies. The Incomplete Pairwise Comparison (IPC) technique developed by Harker [1,2] aims at reducing this effort by ordering the questions in decreasing informational value and by stopping the process when added value of questions decreases below a certain level. This paper proposes further opportunities for effort reduction through globally effective elicitation process. A simple example demonstrates impressive savings in the number of comparisons a decision maker is required to make when using the AHP for complex problems.
@article{milletGloballyEffectiveQuestioning1990,
  title = {Globally Effective Questioning in the {{Analytic Hierarchy Process}}},
  author = {Millet, Ido and Harker, Patrick T.},
  year = {1990},
  month = sep,
  volume = {48},
  pages = {88--97},
  issn = {0377-2217},
  doi = {10.1016/0377-2217(90)90065-j},
  abstract = {A drawback in the use of the Analytic Hierarchy Process (AHP) is the effort required to complete all pairwise comparisons in large hierarchies. The Incomplete Pairwise Comparison (IPC) technique developed by Harker [1,2] aims at reducing this effort by ordering the questions in decreasing informational value and by stopping the process when added value of questions decreases below a certain level. This paper proposes further opportunities for effort reduction through globally effective elicitation process. A simple example demonstrates impressive savings in the number of comparisons a decision maker is required to make when using the AHP for complex problems.},
  journal = {European Journal of Operational Research},
  keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-14160708,~to-add-doi-URL,ambiguity,comparison,dimensionality-reduction,mathematics,multi-criteria-decision-analysis,uncertainty},
  lccn = {INRMM-MiD:c-14160708},
  number = {1}
}
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