The goal of this book is to combine novel aspects in the research fields of metaheuristics and parallelism. Metaheuristics are approximation methods for optimization problems that try to combine basic heuristic methods such that a search space is efficiently and effectively explored. The class of metaheuristics includes methods like colony optimization, evolutionary computation, genetic algorithms, and simulated annealing.

Although the use of metaheuristics allows a significant reduction of the search time, finding a suitable approximation is still time consuming for industrial problems. Therefore, parallelism is useful not only for reducing to reduce the search time, but also for improving the quality of the solution. An important objective of the book is to make clear that parallel versions of metaheuristics often result in new search orders because of a parallel execution, and the resulting techniques have their own dynamics and properties compared to their sequential counterparts.

The book gives an overview of parallel metaheuristics in 21 chapters written by different authors. The chapters are grouped into three parts. The first part contains four chapters that introduce the two fields of metaheuristics and parallelism for readers not familiar with them. The main part contains 13 chapters describing different parallel metaheuristic--models like parallel genetic algorithms, parallel scatter search, parallel simulated annealing, and parallel tabu search--as well as parallel hybrid metaheuristics. The final part contains four chapters on applications of metaheuristics in telecommunications, bioinformatics, and graph and network problems.

Most chapters contain a methodological first part explaining the specific technique, a second part describing the use of parallel strategies for deriving an efficient implementation, and a final experimental part to help readers understand the advantages and limitations of the methods presented.

The introductory chapters and the systematic structure of the chapters make the book suitable not only for specialists in the field of metaheuristics, but also for readers with basic knowledge of optimization methods and parallelism. The book is also suitable for self-instruction, and for providing a good overview of recent metaheuristic techniques. It can be used as a starting point for developing new parallel versions of the methods.