Group AHP framework based on geometric standard deviation and interval group pairwise comparisons

The complexity of multi-criteria decision problems requires the involvement of a group of experts, who can contribute their knowledge, experience and opinions to the decision -making process. The aim of this study is to present a new group analytic hierarchy process (AHP) framework, called GSD-IJ. The main idea is to emphasize group satisfaction with the final decision, which is measured by the group satisfaction index. GSD-IJ is based on geo-metric mean and geometric standard deviation and allows aggregation of individual scalar valued judgments into interval group judgments. The width of the group interval judg-ments is controlled by the parameter k, which ensures the acceptable degree of uncertainty of interval judgments, while providing the highest possible value of the group satisfaction index. Fuzzy preference programming is used to derive scalar-valued group weights from group interval pairwise comparison matrix. Three examples are given to evaluate and val-idate GSD-IJ. The results show that GSD-IJ performs well and is suitable for solving group multi-criteria decision problems.(c) 2023 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Automated summary

This study presents a new group analytic hierarchy process (AHP) framework called GSD-IJ, which emphasizes group satisfaction with the final decision. GSD-IJ uses geometric mean and geometric standard deviation to aggregate individual scalar valued judgments into interval group judgments. The width of the group interval judgments is controlled by the parameter k, ensuring an acceptable degree of uncertainty while maximizing the group satisfaction index.