search, ant colonies, bee colonies, artificial immune systems) for optimization problems * Designing efficient metaheuristics for multi-objective optimization problems * Designing hybrid, parallel, and distributed metaheuristics * Implementing metaheuristics on sequential and parallel machines Using many case studies and treating design and implementation independently, this book gives readers the skills necessary to solve large-scale optimization problems quickly and efficiently. It is a valuable reference for practicing engineers and researchers from diverse areas dealing with optimization or machine learning; and graduate students in computer science, operations research, control, engineering, business and management, and applied mathematics.