Exploitation of a Medium-Sized Fuzzy Outranking Relation Based on Multi-objective Evolutionary Algorithms to Derive a Ranking

Abstract

We present a multi-objective evolutionary algorithm to exploit a medium-sized fuzzy outranking relation to derive a partial order of classes of alternatives (we call it RP-NSGA-II). To measure the performance of RP-NSGA-II, we present an empirical study over a set of simulated multi-criteria ranking problems. The result of this study shows that RP-NSGA-II can effectively exploit a medium-sized fuzzy outranking relation. Finally, we present a real-case study for ranking the municipalities of the state of Guanajuato, Mexico by their levels of marginalization.

Keywords

• Multi-criteria Decision Analysis
• Outranking Relations
• Multi-objective Evolutionary Algorithms
• Ranking Procedures