| Abstract: | Solving multicriteria decision making problems often requires the assessment of certain preferential information. In some occasions, this information must be given by several individuals or social groups, and these individual assessments need to be aggregated into single global preferences. This cardinal preferences aggregation problem has been tackled using different techniques, including multicriteria decision making ones. In this paper, a Meta-Goal Programming approach is proposed, where different target values can be set on several achievement functions that measure the goodness of the global assessments. This methodology presents strong advantages due to its modeling flexibility and its ability to find balanced solutions. The proposed approach is demonstrated with an illustrative example and a series of computational experiments, and it is shown that the Meta-Goal Programming method produces results with better values of the achievement functions than other classical and multicriteria approaches. |
