The use of meta-models has a long tradition in the field of evolutionary computation. However, it is not well studied in the field of evolutionary multiobjective optimization.
In this paper, we present a multiobjective evolutionary algorithm with local meta-models and compare its performance to traditional multiobjective evolutionary algorithms.