Parallel Metaheuristics: A New Class of Algorithms

Enrique Alba

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Description:

With the proliferation of parallel computers and faster community networks, parallel metaheuristics are an effective alternative to speed up the search for approximate solutions of optimizations problems and allow solving larger problems while leading to more efficient algorithms.

Parallel Metaheuristics provides a single, up-to-date reference on parallel metaheuristic issues:

  • Edited single source to fill a gap on metaheuristics by discussing parallelism (contributors are authors of outstanding cutting-edge works in the field)
  • Includes sequential and parallel techniques, up-to-date modern optimization and learning procedures, and complex applications.
  • Real-world problem solutions throughout
  • For researchers in the field and with introductory parts suited for beginners

 

Table of Contents:

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.