A Surrogate Multiobjective Evolutionary Strategy with Local Search and Pre-Selection

Abstrakt

In this paper we present an evolutionary strategy for multi-objective 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 pro-posed algorithm is compared to some of existing evolution-ary algorithms from the literature.

Klíčová slova

• Multiobjective optimization
• meta-model
• evolutionary al-gorithm