Explaining Results of Multi-Criteria Decision Making
Abstract
We introduce a method for explaining the results of various linear and hierarchical multi-criteria decision-making (MCDM) techniques such as WSM and AHP. The two key ideas are (A) to maintain a fine-grained representation of the values manipulated by these techniques and (B) to derive explanations from these representations through merging, filtering, and aggregating operations. An explanation in our model presents a high-level comparison of two alternatives in an MCDM problem, presumably an optimal and a non-optimal one, illuminating why one alternative was preferred over the other one. We show the usefulness of our techniques by generating explanations for two well-known examples from the MCDM literature. Finally, we show their efficacy by performing computational experiments.
Cite
@article{arxiv.2209.04582,
title = {Explaining Results of Multi-Criteria Decision Making},
author = {Martin Erwig and Prashant Kumar},
journal= {arXiv preprint arXiv:2209.04582},
year = {2022}
}