Metaheuristics exhibit desirable properties like simplicity, easy parallelizability, and ready applicability to different
types of optimization problems. After a comprehensive introduction to the field, the contributed chapters in this book include
explanations of the main metaheuristics techniques, including simulated annealing, tabu search, evolutionary algorithms, artificial
ants, and particle swarms, followed by chapters that demonstrate their applications to problems such as multiobjective optimization,
logistics, vehicle routing, and air traffic management.
The authors are leading researchers in this
domain, with considerable teaching and applications experience, and the book will be of value to industrial practitioners,
graduate students, and research academics.