The influence on partial order ranking from input parameter uncertainty - Definition of a robustness parameter

The method of partial order ranking has been used within the environmental area for a variety of purposes as an attractive way of handling complex inf ormation. However, the environmental data are often associated with a signi ficant degree of uncertainty. In this investigation the general nature of t he influence from data uncertainty on the partial order ranking is analyzed . A Monte Carlo type analysis is performed in which a series of randomly fo rmed data are used to test the influence of data uncertainty. The partial o rder ranking is interpreted, where the results are transferred to a one-dim ensional ranking scale taking into account that not all elements are ranked with the same certainty. A simple general robustness parameter (E) in form of the expected number of comparisons for each ranking element is defined and correlated to the uncertainty analysis results. A simple equation relat es E to the number of elements and the number of parameters, respectively. The magnitude of the ranking uncertainty is shown to increase rapidly when the E value decreases below 4-5 comparisons per element. When the E value e xceeds 5 the ranking uncertainty becomes nearly constant and independent on the actual E value. (C) 2000 Elsevier Science Ltd. All rights reserved.