Identification of Homogeneous Groups of Actors in a Local AHP-Multiactor Context with a High Number of Decision-Makers: A Bayesian Stochastic Search

Abstract

The identification of homogeneous groups of actors in a local AHP-multiactor context based on their preferences is an open problem, particularly when the number of decision-makers is high. To solve this problem in the case of using stochastic AHP, this paper proposes a new Bayesian stochastic search methodology for large-scale problems (number of decision-makers greater than 20). The new methodology, based on Bayesian tools for model comparison and selection, takes advantage of the individual preference structures distributions obtained from stochastic AHP to allow the identification of homogeneous groups of actors with a maximum common incompatibility threshold. The methodology offers a heuristic approach with several near-optimal partitions, calculated by the Occam’s window, that capture the uncertainty that is inherent when considering intangible aspects (AHP). This uncertainty is also reflected in the graphs that show the similarities of the decision-maker’s opinions and that can be used to achieve representative collective positions by constructing agreement paths in negotiation processes. If a small number of actors is considered, the proposed algorithm (AHP Bayesian clustering) significantly reduces the computational time of group identification with respect to an exhaustive search method. The methodology is illustrated by a real case of citizen participation based on e-Cognocracy.

Multicriteria sorting method based on global and local search for supplier segmentation

“…Nevertheless, recent literature provides examples where multicriteria and mining evaluations are integrated into the trace clustering problem, where using noncompensatory similarity measures and a normalised spectral clustering algorithm, they obtain classifications that reflect the preferences of the decision-maker in an initial multicriteria environment (Delias et al, 2023). Other authors have integrated multicriteria methods (local AHP-Analytic Hierarchy Process) and Bayesian clustering to identify homogeneous groups of citizens for group decision-making (Altuzarra et al, 2019(Altuzarra et al, , 2022. Han et al (2020) include decision-makers' preferences by measuring the importance of the criteria with AHP and then using a linguistic fuzzy clustering method.…”

Using Fuzzy Comprehensive Evaluation to Assess the Competency of Full-Time Water Conservancy Emergency Rescue Teams

“…AHP is a method for decomposing the factors related to decision-making into levels of objectives, criteria, schemes, etc., and analyzing them layer by layer on this basis [42,43]. In this part of the study, AHP was used to obtain the weights of assessment indicators for a competency assessment indicator system.…”