A novel hybrid evolutionary strategy and its periodization with multi-objective genetic optimizers

This work investigates the effects of the periodization of local and global multi-objective search algorithms. To this, we introduce a model for periodization and define a new multi-objective evolutionary algorithm adopting concepts from Evolutionary Strategies and NSGAII. We show that our method, especially when periodized with standard multi-objective genetic algorithms, excels for the evolution of digital circuits on the Cartesian Genetic Programming model as well as on some standard benchmarks such as the ZDT6.