  Parameter control aims at realizing performance gains through a dynamic
choice of the parameters which determine the behavior of the underlying
optimization algorithm. In the context of evolutionary algorithms this research
line has for a long time been dominated by empirical approaches. With the
significant advances in running time analysis achieved in the last ten years,
the parameter control question has become accessible to theoretical
investigations. A number of running time results for a broad range of different
parameter control mechanisms have been obtained in recent years. This book
chapter surveys these works, and puts them into context, by proposing an
updated classification scheme for parameter control.
