Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
405023 | Knowledge-Based Systems | 2014 | 7 Pages |
Abstract
We consider a multicriteria decision-making context in which the decision-maker’s preferences are represented by a multi-attribute additive value function. We account for imprecision concerning the performance of alternatives, value functions and weights, which represent the relative importance of criteria. We propose two new methods based on dominance intensity measures aimed at ranking alternatives. Both methods can be applied to different representations of imprecision about weights. Their performance is compared with other existing approaches when ordinal weight information represents imprecision concerning weights. Monte Carlo simulation is used for the comparison in terms of a hit ratio and a rank-order correlation.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
A. Mateos, A. Jiménez-Martín, E.A. Aguayo, P. Sabio,