PROMETHEE for prioritized criteria

In most cases, PROMETHEE method just applies to traditional multicriteria decision making (MCDM) problems with independent criteria. However, there exist more or less interdependences among criteria in actual situations. A special case is MCDM with prioritizations among criteria, called prioritized MCDM. In recent years, how to deal with MCDM problems in the environment of prioritized criteria becomes hot topic increasingly. Lots of existing methods, especially some methods based on aggregated operators, are modified for the prioritized MCDM. However, up to now, PROMETHEE methods are not very mature when used into prioritized MCDM problems. Therefore, our purpose is to modify traditional PROMETHEE methods according to prioritized MCDM after considering the characteristics of both PROMETHEE methods and prioritized criteria. Firstly, preference information is not static any longer for prioritized criteria, so we design an approach to weight the criteria dynamically based on a new concept—preference expectations. Furthermore, an ordered weighted averaging operator is used to generate pseudo-criteria for the situation of weakly ordered prioritizations. In such a case, the situation of weakly ordered prioritizations is transformed into that of strictly ones. After quantifying preference information properly, we can then calculate aggregated preference indices which are important intermediate outcomes for PROMETHEE to rank alternatives. An example, for assessing the strategic status of islands and reefs, is taken to illustrate the practicability and feasibility of our method.