EAs are powerful optimization methods, able to handle any kind of fitness function: irregular objective and constraints, multi-objective, ... But it will be argued that EAs can be more than just another optimization method thanks to their ability to deal with any kind of representation, i.e. to search any kind of search space.
These arguments will be developed (in English :-) on examples of real-world successful applications, addressing both large scale combinatorial optimization problems, (e.g. scheduling) and engineering problems (e.g. system identification and design).
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