Heuristic Rating Estimation Method for the incomplete pairwise comparisons matrices
This work provides an incremental improvement to decision-making methods by reducing expert workload and costs in ranking alternatives.
The paper tackles the problem of incomplete pairwise comparison matrices in decision-making by extending existing additive and multiplicative methods to work with partial expert comparisons, eliminating the need for experts to compare all alternatives pairwise. This reduces data collection costs and shortens the decision-making process.
The Heuristic Rating Estimation Method enables decision-makers to decide based on existing ranking data and expert comparisons. In this approach, the ranking values of selected alternatives are known in advance, while these values have to be calculated for the remaining ones. Their calculation can be performed using either an additive or a multiplicative method. Both methods assumed that the pairwise comparison sets involved in the computation were complete. In this paper, we show how these algorithms can be extended so that the experts do not need to compare all alternatives pairwise. Thanks to the shortening of the work of experts, the presented, improved methods will reduce the costs of the decision-making procedure and facilitate and shorten the stage of collecting decision-making data.