8.6.2 Advantages and Disadvantages of Evolutionary Algorithm Optimizers

Evolutionary algorithm optimizers are global optimization methods and scale well to higher dimensional problems. They are robust with respect to noisy evaluation functions, and the handling of evaluation functions which do not yield a sensible result in given period of time is straightforward.

The algorithms can easily be adjusted to the problem at hand. Almost any aspect of the algorithm may be changed and customized. On the other hand, although lots of research has been done on which evolutionary algorithm is best suited for a given problem, this question has not been answered satisfactorily. While the standard values usually provide reasonably good performance, different configurations may give better results. Furthermore, premature convergence to a local extremum may result from adverse configuration and not yield (a point near) the global extremum.