AHP Under Uncertainty: A Modified Version of Cloud Delphi Hierarchical Analysis

Abstract

Cloud Delphi Hierarchical Analysis (CDHA) is an Analytic Hierarchical Process (AHP) based method for group decision making under uncertain environments. CDHA adopts appropriate tools for such environments, namely Delphi method, and Cloud model. Adopting such tools makes it a promising AHP variant in handling uncertainty. In spite of CDHA is a promising method, it is still suffering from two main defects. The first one lies in its definition of the consistency index, the second one lies in the technique used in building the pairwise comparisons Cloud models. This paper will discuss these defects, and propose a modified version. To overcome the defects mentioned above, the modified version will depend more on the context of the interval pairwise comparisons matrix while building the corresponding Cloud pairwise comparisons matrix. A simple case study that involves reproducing the relative area sizes of four provinces in Syria will be used to illustrate the modified version and to compare it with the original one.