Interaction-driven aggregation of multiple numeric indicators with applications to decision-making support systems

Abstract

The article discusses the topic of combining various numerical indicators (indexes, models, scales, etc.) into a new synthetic index, which will allow for effective decision making within the expert system. Mentioned problem already has a well-researched solution based on aggregation operators. However, the aggregation-based approach did not create a new, consistent decision-making index. Moreover, some problems may occur because the interaction between input data is omitted during the aggregation. The methods proposed in this paper will focus on the possibility of maintaining interactions between attributes. The described methods will then be applied to the real-life problem of monitoring and assessment of maintenance in an enterprise.