Improving consistency evaluation in fuzzy multi-attribute pairwise comparison-based decision-making methods

Improving consistency evaluation in fuzzy multi-attribute pairwise comparison-based decision-making methods

A typical approach to handle the complexity of multi-faceted decision-making problems is to use multi-attribute decision-making (MADM) methods based on pairwise comparisons. Fuzzy set theory has also been employed to cope with the uncertainty and vagueness involved in conducting the comparisons between components of a decision model. An important issue regarding the reliability of the output is the consistency of pairwise comparisons provided by the decision maker(s). Using the MADM method developed by Lu et al. (2007) as a foundation, this paper proposes an algorithm for evaluating the consistency level of pairwise comparison matrices, where linguistic data are used. A crisp numeric scale has been introduced to consider the priority of linguistic data and to avoid the complexity of handling fuzzy calculations in consistency evaluation of pairwise comparison matrices. As an advantage, the proposed method of consistency evaluation is capable of assessing the degree of inconsistency among the pairwise comparisons. Therefore, the acceptance or rejection of the pairwise comparisons can be determined based on the desired degree of tolerance in accepting inconsistent judgments. An application of a revised MADM method is then demonstrated in a case study involving flood mitigation project selection in Australia.

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