Evolutionary Computation

This book presents several recent advances on Evolutionary Computation, specially evolution-based optimization methods and hybrid algorithms for several applications, from optimization and learning to pattern recognition and bioinformatics. Concerning evolutionbased optimization methods, this book presents diverse versions of genetic algorithms, genetic programming,and performance studies and analyses, as well as several particle swarm optimizers and hybrid approaches using neural networks and artificial immunological systems for multi-objective optimization. This book also presents new algorithms based on several analogies and metafores, where one of them is based on philosophy, specifically on the philosophy of praxis and dialectics. In this book it is also presented interesting applications on bioinformatics, specially the use of particle swarms to discover gene expression patterns in DNA microarrays. Therefore, this book features representative work on the field of evolutionary computation and applied sciences. The intended audience is graduate, undergraduate, researchers, and anyone who wishes to become familiar with he latest research work on this field. The contents of this book allow the reader to know more both theoretical and technical aspects and applications of evolutionary computation.