Springer Hybrid Metaheuristics: 434 (Studies in Computational Intelligence, 434)

This book provides a complete background for designing and implementing hybrid metaheuristics to solve complex optimization problems - continuous/discrete, mono-objective/multi-objective, optimization under uncertainty - in a wide range of application domains. Review From the book reviews:“Hybrid Metaheuristics is an excellent manuscript for a reader who wants to understand state-of-the-art hybrid metaheuristics and their applications. … this book could be a source of inspiration for those looking for new procedures for hybridizing metaheuristics and new application areas for metaheuristic techniques. … a good reference for researchers, practitioners, and students of operations research or computer science who want to have a complete view of metaheuristics and the process of obtaining new procedures by hybridization.” (Javier Faulin, Interfaces, Vol. 44 (5), September-October, 2014) From the Back Cover The main goal of this book is to provide a state of the art of hybrid metaheuristics. The book provides a complete background that enables readers to design and implement hybrid metaheuristics to solve complex optimization problems (continuous/discrete, mono-objective/multi-objective, optimization under uncertainty) in a diverse range of application domains. Readers learn to solve large scale problems quickly and efficiently combining metaheuristics with complementary metaheuristics, mathematical programming, constraint programming and machine learning. Numerous real-world examples of problems and solutions demonstrate how hybrid metaheuristics are applied in such fields as networks, logistics and transportation, bio-medical, engineering design, scheduling.