Memetic algorithms are evolutionary algorithms that apply a local search process to refine solutions to hard problems. Memetic algorithms are the subject of intense scientific research and have been successfully applied to a multitude of real-world problems ranging from the construction of optimal university exam timetables, to the prediction of protein structures and the optimal design of space-craft trajectories. This monograph presents a rich state-of-the-art gallery of works on Memetic algorithms being the first book focusing on Memetic algorithms as the central topical matter. This book gives a coherent, integrated view on both good practice examples and new trends including a concise and self-contained introduction to Memetic Algorithms. It is a necessary read for postgraduate students and researchers interested in recent advances in search and optimization technologies based on Memetic algorithms, but can also be used as complement to undergraduate textbooks on artificial intelligence.