A new evolutionary technique for multicriteria optimization called Guiding Hyper-plane Evolutionary Algorithm (GHEA) is proposed. The originality of the approach consists in the fact that the fitness assignment is realized by using a guiding hyperplane and a new non Pareto optimality concept. Numerical experiments illustrate the performance of GHEA compared with the popular NSGA-II and SPEA2. Categories and Subject Descriptors I.2.8 [Artificial Intelligence]: Problem Solving, Control Methods, and Search—Heuristic methods General Terms Algorithms Keywords evolutionary multiobjective optimization, guiding hyperplane
Corina Rotar, D. Dumitrescu, Rodica Ioana Lung