Abstract:
Evolutionary Algorithms (EAs) can be applied to almost any optimization or learning problem by making some simple customizations to the underlying represen- tation and/or reproductive operators. This makes them an appealing choice when facing a new or unusual problem. Unfortunately, while making these changes is often easy, getting a customized EA to operate effectively (i.e. find a good solution quickly) can be much more difficult.
