The "Handbook of Memetic Algorithms" offers a comprehensive and structured overview of the development and application of memetic algorithms (MAs) in the field of computational intelligence. MAs combine various operators to solve complex optimization problems. This specialized book addresses the key findings and advancements in this area since the first definition of MAs. It provides a broad analysis of different algorithmic solutions and their successful applications. The authors examine specific classes of optimization problems, including constrained and multi-objective optimization, as well as continuous and combinatorial problems. For each problem, memetic approaches to tackle the challenges are presented, supplemented by practical examples. The careful editing by the editors ensures that the book remains coherent and informative despite the multitude of authors. It is aimed not only at researchers but also at practitioners and engineers who need to solve real-world optimization problems, and it is also of interest to students and researchers in related fields.