Evolutionary computation can be viewed as a set of techniques conceptually inspired by biological processes. Among that techniques, one of the most used are genetic algorithms. They follow the Darwin Law''s to find the solution of a problem. The overall objective of this book is to provide a "roadmap" with which to find the way toward finding computational solutions to various problems. To this end, a general introduction is presented of the methods and techniques associated with genetic algorithms. In this context, this book ought not be viewed as an exhaustive or comprehensive analysis of the techniques presented herein. Instead, it should be considered as a reference that introduces the terminology, key concepts, and basic bibliography that can serve as a starting point such that the reader will be better equipped to subsequently pursue more deeply those topics that may be of special interest. In particular, this book is designed for those people who are interested in new approaches to problem solving as well for researchers who hope to initiate research directions along the lines of evolutionary computing or closely connected areas.

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M. Gestal and D. Rivero are PhD in Computer Science and associate professors at the University of A Coruña. A. Pazos, Full Professor at the same University, is PhD in Medicine and PhD in Computer Science. They work with Evolutionary Computation techniques in general and with GGAA in particular.