Algorithms for solving hard optimization problems typically have several parameters that
need to be set appropriately such that some aspect of performance is optimized. In this …

This is the second edition of our 2003 book. It is primarily a book for lecturers and graduate
and undergraduate students. To this group the book offers a thorough introduction to …

Memetic Algorithms (MAs) are computational intelligence structures combining multiple and
various operators in order to address optimization problems. The combination and …

Algorithm configuration (AC) is concerned with the automated search of the most suitable
parameter configuration of a parametrized algorithm. There is currently a wide variety of AC …

Tuning the parameters of an evolutionary algorithm (EA) to a given problem at hand is
essential for good algorithm performance. Optimizing parameter values is, however, a non …

Finding appropriate parameter values for evolutionary algorithms (EA) is one of the
persisting grand challenges of the evolutionary computing (EC) field. In general, EC …

This book is the result of a very long journey into optimization, and, more specifically, into
evolutionary computation. This journey would not have been possible without the support of …

Autonomous search is a particular case of adaptive systems that improve their solving
performance by modifying and adjusting themselves to the problem at hand, either by self …

Finding appropriate parameter values for Evolutionary Algorithms (EAs) is one of the
persistent challenges of Evolutionary Computing. In recent publications we showed how the …

Tuning evolutionary algorithms is a persistent challenge in the field of evolutionary
computing. The efficiency of an evolutionary algorithm relates to the coding of the algorithm …