A surrogate multiobjective evolutionary strategy with local search and pre-selection
Martin Pilát, Roman Neruda · 2012
In this paper we present an evolutionary strategy for multiobjective optimization. This evolution strategy is based on a surrogate memetic operator and a surrogate preselection model which provides several individuals in each generation. Thus, the optimization may be easily parallelized. The proposed algorithm is compared to some of existing evolutionary algorithms from the literature.