Part I: Contextual Issues -- 1. The Generalized Assignment Problem -- 2. Automatic Design for Matheuristics -- Part II: Metaheuristic Hybrids -- 3. Single Solution Metaheuristics -- 4. Population-Based metaheuristics -- Part III: Original Matheuristics -- 5. Diving Heuristics -- 6. Very Large-Scale Neighborhood Search -- 7. Decomposition Based Heuristics -- 8. Corridor Method -- 9. Kernel Search -- 10. Fore-and-Back.

This book is the first comprehensive tutorial on matheuristics. Matheuristics are based on mathematical extensions of previously known heuristics, mainly metaheuristics, and on original, area-specific approaches. This tutorial provides a detailed discussion of both contributions, presenting the pseudocodes of over 40 algorithms, abundant literature references, and for each case a step-by-step description of a sample run on a common Generalized Assignment Problem example. C++ source codes of all algorithms are available in an associated SW repository.