On the invalidity of fuzzifying numerical judgments in the Analytic Hierarchy Process
β Scribed by Thomas L. Saaty; Liem T. Tran
- Publisher
- Elsevier Science
- Year
- 2007
- Tongue
- English
- Weight
- 442 KB
- Volume
- 46
- Category
- Article
- ISSN
- 0895-7177
No coin nor oath required. For personal study only.
β¦ Synopsis
Fuzzy set theory has serious difficulties in producing valid answers in decision-making by fuzzifying judgments. No theorems are available about its workability when it is applied indiscriminately as a number crunching approach to numerical measurements that represent judgments. When judgments are allowed to vary in choice over the values of a fundamental scale, as in the Analytic Hierarchy Process, these judgments are themselves already fuzzy. To make them fuzzier can make the validity of the outcome, when the actual outcome is known, worse, as shown by several examples in this paper. Also, improving the consistency of a judgment matrix does not necessarily improve the validity of the outcome. Validity is the goal in decision-making, not consistency, which can be successively improved by manipulating the judgments as the answer gets farther and farther from reality. An example of this is included.
π SIMILAR VOLUMES
In this paper we apply multiattribute value theory as a framework for examining the use of pairwise comparisons in the analytic hierarchy process (AHP). On one hand our analysis indicates that pairwise comparisons should be understood in terms of preference differences between pairs of alternatives.
## In paired comparisons, the individuals in a number of groups giving their judgments are examined for agreement among themselves. Statistical methods are applied to see whether these groups are significantly different in giving their judgments or not. When individual judgments are homogeneous, a