Complementary selection and variation for an efficient multiobjective optimization of complex systems

Real-world applications generally distinguish themselves from theoretical developments in that they are much more complex and varied. As a consequence, better models require more details, new methods and, finally, more complexity. By confronting a benchmark evolutionary algorithm with an automotive gearbox with hundreds of parameters to optimize, we were able to observe new requirements which led us to an additional procedure.

• Type: Conference
• Year: 2005
• Where: CEC
• Authors: Benoît Bagot, Hartmut Pohlheim
• Keywords: Artificial Intelligence, Benchmark Evolutionary Algorithm, CEC 2005, Real-world Applications, Theoretical Developments