Incomplete Analytic Hierarchy Process (Ahp) Solution Methodologies

Official URL: https://risc01.sabanciuniv.edu/record=b3205830

Analytic hierarchy process (AHP) is a well-known multi criteria decision making method. It relies on matrices constructed through pairwise comparisons of criteria and alternatives by decision makers. In the literature, AHP has been proven effective in assessing weights of criteria and/or relative scores of alternatives. However, in order to utilize the AHP method, it is necessary for the decision maker to determine complete matrices, meaning that the decision maker must assign all pairwise comparisons into the matrices. This requirement may not always be feasible due to reasons such as the decision maker's inadequate knowledge in certain pairwise comparisons, uncertainty in the pairwise comparisons, and time constraints. In the literature, several algorithms have been proposed to address this issue, but there is no consensus on the best algorithm. In this study, we provided a comparative analysis of the existing algorithms. Furthermore, we also introduced new parametric heuristic algorithms for the incomplete AHP framework. The proposed algorithms were also compared with the existing algorithms in different experimental conditions. The performances of these methods were assessed utilizing metrics from the literature as well as a metric developed for the incomplete AHP framework in this research. The comparisons were conducted in two types of experiments, i.e., numerical and empirical. According to the results of these experiments, the developed algorithms were competitive, and even demonstrated better performance under some experimental conditions.