An agent-oriented decision support system combining fuzzy clustering and the AHP

Decision making is a complex process, particularly when it is carried out by multidisciplinary team. Methods based on the analytical hierarchy process have been widely employed because they provide solid mathematical background. Nevertheless, solutions such as the Aggregation of Individual Judgements (AIJ) and the Aggregation of Individual Priorities (AIP) do not offer sufficient explanatory data in regards with the final decision. We developed an agent-based decision support system (DSS) that employs fuzzy clustering to group individual evaluations and the AHP to reach a final decision. Fuzzy clustering is adequate to determine important pieces of data such as the largest group of evaluations that exist around a centroid value. On the other hand, the MAS paradigm offers capabilities for achieving distributed and asynchronous processing of data. The AHP is used after the individual evaluations are clustered, as if the group were a single evaluator. Altogether, the proposed solution enhances the quality of multi-criteria group decision making.

Research highlights
► We present a decision support system based on multiple agents.
► Our model is based on the analytical hierarchy process.
► We employ fuzzy c-means to compute decision clusters.
► A solution for the problem of group decision making is provided.