Journal Article

Fuzzy analytic hierarchy process with ordered pair of normalized real numbers

Zhang, Hui, Li, Bo, Cui, Haoyang, Yang, Chunming, Zhao, Xujian, Zhou, Lei

2023

Overview

The Analytic hierarchy process (AHP) is a widely used multi-criteria decision theory, and most AHP relies on the judgments of experts to derive priority scales. However, the judgments of experts may be subjective. Using machine learning algorithms for decision-making can be more objective, but machine learning algorithms are strongly related to the collected data and not being flexible enough. This paper tries to combine experts’ judgments with algorithmic judgments to improve the bias of experts’ judgments while still making decision-making flexible. In this paper, the authors introduce the ordered pair of normalized real numbers (OPNs) into the AHP method for the first time and propose the fuzzy analytic hierarchy process with the OPNs (OFAHP). The OFAHP uses OPNs to combine experts’ judgments with those of machine learning algorithms and then make decisions by OPNs. Experiments on real data sets show that the proposed method can get reasonable decision results. Moreover, when the experts’ judgments are wrong or invalid, the judgments given by the machine learning algorithm can correct the experts’ judgments to obtain a reasonable decision-making result.

• Publisher: Springer Berlin Heidelberg,Springer Nature B.V
• Subject: Algorithms / Analytic hierarchy process / Artificial Intelligence / Computational Intelligence / Control / Data collection / Decision analysis / Decision making / Decision theory / Decision trees / Engineering / Fuzzy sets / Hierarchies / Judgments / Machine learning / Mathematical analysis / Mathematical Logic and Foundations / Mechatronics / Methods / Multiple criteria decision making / Multiple criterion / Preferences / Real numbers / Robotics / Set theory / Soft Computing in Decision Making and in Modeling in Economics