engleski

Application of PageRank Centrality in Multi- Criteria Decision Making

Multicriterial analysis is a highly developed area since there is a large number of multicriteria decision-making (MCDM) methods. The multi-criteria analysis enables a precise problem analysis and ensures the rationality of decision that is made. However, all problem analysis using different methods can give different results (decision), so it is important to recognize which MCDM method is appropriate for a particular situation. There are MCDM methods by using which we can model dependencies and influences between the criteria in decision-making problem. One of the most used MCDM methods that are used in terms of problem analysis is the analytic network process (ANP). Previous researches discussed some problems related to using the ANP in decision-making. As a solution to those problems using the PageRank centrality can be considered. In this paper, we are presenting several possibilities of applying the PageRank centrality for multi-criteria analysis. Presented possibilities are compared and discussed. As a result, using the weighted PageRank centrality is proposed as the optimal solution for multi-criteria analysis when dependencies (influences) between the criteria are examined.

criteria ; multi-criteria decision-making ; MCDM ; ANP ; PageRank centrality ; PageRank ; influences ; dependencies

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