A multi-objective extension of the net flow rule for exploiting a valued outranking relation

摘要

This paper presents a multiobjective extension of the net flow rule for solving multicriteria ranking problems: how to rank a set of alternatives when the aggregation model of preferences is a known valued outranking relation in a decreasing order of preference. When the aggregation model of preferences is based on the outranking approach, special treatment is required, but some non-consistent situations of the explicit global model of preferences could happen. In this case, the exploitation phase could then be treated as a multiobjective optimisation problem. In this way, a number of solutions can be found that provide the decision-maker with insight into the characteristics of the problem before a final solution is chosen. We present a multiobjective evolutionary algorithm for improving the quality of a recommendation when a valued outranking relation is exploited; the performance of the algorithm is evaluated on a set of test problems. Our computational results show that the multiobjective genetic algorithm-based heuristic is capable of producing high-quality recommendations.