Detecting and adjusting ordinal and cardinal inconsistencies through a graphical and optimal approach in AHP models

Han-Lin Li, Li Ching Ma*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

69 Scopus citations

Abstract

An AHP model suffering from significant cardinal or/and ordinal inconsistencies in its preference matrix is difficult to rank rationally the alternatives. This study proposes an iterative method to assist a decision maker to detect/adjust inconsistencies and to represent his/her judgments properly. A Gower plot is first used to detect ordinal and cardinal inconsistencies. Two optimization models are then constructed to provide suggeted adjustments upon the request of the decision maker. By examining the Gower plots and numerical suggestions, the decision maker may revise iteratively the preference ratios to improve inconsistencies until all alternatives are ranked.

Original languageEnglish
Pages (from-to)780-798
Number of pages19
JournalComputers and Operations Research
Volume34
Issue number3
DOIs
StatePublished - Mar 2007

Keywords

  • AHP
  • Gower plot
  • Inconsistency
  • Interactive
  • Preference

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