Multiobjective evolutionary algorithms: Pareto rankings

Abstract

In this work we present two new Pareto based ranking methods. We compare them with three classical ones due to Belegundu, Goldberg and Fonseca and Fleming. Furthermore, we introduce the problem of classification errors. One of the proposed methods outperforms the others in five out of seven test problems.