Article ID: | iaor20117516 |
Volume: | 54 |
Issue: | 7-8 |
Start Page Number: | 1785 |
End Page Number: | 1790 |
Publication Date: | Oct 2011 |
Journal: | Mathematical and Computer Modelling |
Authors: | Izquierdo J, Bentez J, Delgado-Galvn X, Gutirrez J A |
Keywords: | artificial intelligence: decision support |
The various mechanisms that represent the know‐how of decision‐makers are exposed to a common weakness, namely, a lack of consistency. To overcome this weakness within AHP (analytic hierarchy process), we propose a framework that enables balancing consistency and expert judgment. We specifically focus on a linearization process for streamlining the trade‐off between expert reliability and synthetic consistency. An algorithm is developed that can be readily integrated in a suitable DSS (decision support system). This algorithm follows an iterative feedback process that achieves an acceptable level of consistency while complying to some degree with expert preferences. Finally, an application of the framework to a water management decision‐making problem is presented.