Parallel Metaheuristics : A New Class of Algorithms Book

Foreword.

Preface

Contributors.

PART I: INTRODUCTION TO METAHEURISITICS AND PARALLELISM.

1. An Introduction to Metaheuristic Techniques (C. Blum, et al.).

2. Measuring the Performance of Parallel Metaheuristics (E. Alba & G. Luque).

3. New Technologies in Parallelism (E. Alba & A. Nebro).

4. Metaheuristics and Parallelism (E. Alba, et al.). 

PART II: PARALLEL METAHEURISTIC MODELS.

5. Parallel Genetic Algorithms (G. Luque, et al.).

6. Parallel Genetic Programming (F. Fernández, et al.).

7. Parallel Evolution Strategies (G. Rudolph).

8. Parallel Ant Colony Algorithms (S. Janson, et al.).

9. Parallel Estimation of Distribution Algorithms (J. Madera, et al.).

10. Parallel Scatter Search (F. Garcia, et al.).

11. Parallel Variable Neighborhood Search (J. Moreno-Pérez, et al.).

12. Parallel Simulated Annealing (M. Aydin, V. Yigit).

13. Parallel Tabu Search (T. Crainic, et al.).

14. Parallel Greedy Randomized Adaptive Search Procedures (M. Resende & C. Ribeiro).

15. Parallel Hybrid Metaheuristics (C. Cotta, et al.). 

16. Parallel MultiObjective Optimization (A. Nebro, et al.).

17. Parallel Heterogeneous Metaheuristics (F. Luna, et al.).

PART III: THEORY AND APPLICATIONS.

18. Theory of Parallel Genetic Algorithms (E. Cantú-Paz).

19. Parallel Metaheuristics Applications (T. Crainic & N. Hail).

20. Parallel Metaheuristics in Telecommunications (S. Nesmachnow, et al.).

21. Bioinformatics and Parallel Metaheuristics (O. Trelles, A. Rodriguez).

Index.