00000cmm a22000004a 4500 UP-99796217611212027 Buklod 20140423145211.0 m go j cr cn |||aaaaa 110713s2011 xx u | eng d 9783642220845 (eBook) 3642220843 (eBook) (iLib)UPD-00214608175 DLC DML eng DMLUC QA 402.5 L87 2011eb Luque, Gabriel Parallel genetic algorithms [electronic resource] theory and real world applications Gabriel Luque and Enrique Alba. Berlin Springer-Verlag c2011. 1 online resource (xii, 171 p.) ill. Studies in Computational Intelligence 367 Part I Introduction -- Part II Characterization of Parallel Genetic Algorithms -- Part III Applications of Parallel Genetic Algorithms. IP-based subscription, access limited to within on-campus computer network. Access via Electronic Resources of the UPD University Library Website. This book is the result of several years of research trying to better characterize parallel genetic algorithms (pGAs) as a powerful tool for optimization, search, and learning. Readers can learn how to solve complex tasks by reducing their high computational times. Dealing with two scientific fields (parallelism and GAs) is always difficult, and the book seeks at gracefully introducing from basic concepts to advanced topics.   The presentation is structured in three parts. The first one is targeted to the algorithms themselves, discussing their components, the physical parallelism, and best practices in using and evaluating them. A second part deals with the theory for pGAs, with an eye on theory-to-practice issues. A final third part offers a very wide study of pGAs as practical problem solvers, addressing domains such as natural language processing, circuits design, scheduling, and genomics.   This volume will be helpful both for researchers and practitioners. The first part shows pGAs to either beginners and mature researchers looking for a unified view of the two fields: GAs and parallelism. The second part partially solves (and also opens) new investigation lines in theory of pGAs. The third part can be accessed independently for readers interested in applications. The result is an excellent source of information on the state of the art and future developments in parallel GAs.   Electronic reproduction. New York SpringerLink 2011. Available via World Wide Web through SpringerLink. Genetic algorithms. Artificial intelligence. Electronic books. Alba, Enrique. SpringerLink (Online service). Available for University of the Philippines Diliman via SpringerLink. Click here to access http://link.springer.com/book/10.1007/978-3-642-22084-5 FO Monograph UPD DMLR UPD DSCI Electronic Resource