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.

• Type: Journal
• Year: 2010
• Where: CEC
• Authors: Paul Kaufmann, Tobias Knieper, Marco Platzner
• Keywords: Artificial Intelligence, CEC 2010, Multi-objective Evolutionary Algorithm, Multi-objective Genetic Algorithms, Multi-objective Search Algorithms