A Multiobjective Evolutionary Algorithm Guided by Averaged Hausdorff Distance to Aspiration Sets
Rudolph G, Schütze O, Grimme C, Trautmann H
The incorporation of expert knowledge into multiobjective optimization is an important issue which in this paper is reflected in terms of an aspiration set consisting of multiple reference points. The behaviour of the recently introduced evolutionary multiobjective algorithm AS-EMOA is analysed in detail and comparatively studied for biobjective optimization problems w.r.t. R-NSGA2 and a respective variant. It will be shown that the averaged Hausdorff distance, integrated into AS-EMOA, is an effcient means to accurately approximate the desired aspiration set.
multi-objective optimization; aspiration set; preferences