Parallel genetic algorithms : theory and real world applications / Gabriel Luque and Enrique Alba

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 book is targeted to the algorithms themselves, discussing their components, the physical parallelism, and best practices in using and evaluating them. It deals with the theory for pGAs, with an eye on theory-to-practice issues. It 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.