Parallel Metaheuristics (eBook, PDF) - Alba, Enrique
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Solving complex optimization problems with parallelmetaheuristics Parallel Metaheuristics brings together an international group ofexperts in parallelism and metaheuristics to provide a much-neededsynthesis of these two fields. Readers discover how metaheuristictechniques can provide useful and practical solutions for a widerange of problems and application domains, with an emphasis on thefields of telecommunications and bioinformatics. This volume fillsa long-existing gap, allowing researchers and practitioners todevelop efficient metaheuristic algorithms to find solutions. The book is…mehr

Produktbeschreibung
Solving complex optimization problems with parallelmetaheuristics Parallel Metaheuristics brings together an international group ofexperts in parallelism and metaheuristics to provide a much-neededsynthesis of these two fields. Readers discover how metaheuristictechniques can provide useful and practical solutions for a widerange of problems and application domains, with an emphasis on thefields of telecommunications and bioinformatics. This volume fillsa long-existing gap, allowing researchers and practitioners todevelop efficient metaheuristic algorithms to find solutions. The book is divided into three parts: * Part One: Introduction to Metaheuristics and Parallelism,including an Introduction to Metaheuristic Techniques, Measuringthe Performance of Parallel Metaheuristics, New Technologies inParallelism, and a head-to-head discussion on Metaheuristics andParallelism * Part Two: Parallel Metaheuristic Models, including ParallelGenetic Algorithms, Parallel Genetic Programming, ParallelEvolution Strategies, Parallel Ant Colony Algorithms, ParallelEstimation of Distribution Algorithms, Parallel Scatter Search,Parallel Variable Neighborhood Search, Parallel SimulatedAnnealing, Parallel Tabu Search, Parallel GRASP, Parallel HybridMetaheuristics, Parallel Multi-Objective Optimization, and ParallelHeterogeneous Metaheuristics * Part Three: Theory and Applications, including Theory of ParallelGenetic Algorithms, Parallel Metaheuristics Applications, ParallelMetaheuristics in Telecommunications, and a final chapter onBioinformatics and Parallel Metaheuristics Each self-contained chapter begins with clear overviews andintroductions that bring the reader up to speed, describes basictechniques, and ends with a reference list for further study.Packed with numerous tables and figures to illustrate the complextheory and processes, this comprehensive volume also includesnumerous practical real-world optimization problems and theirsolutions. This is essential reading for students and researchers in computerscience, mathematics, and engineering who deal with parallelism,metaheuristics, and optimization in general.

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  • Produktdetails
  • Verlag: John Wiley & Sons
  • Seitenzahl: 566
  • Erscheinungstermin: 19.09.2005
  • Englisch
  • ISBN-13: 9780471739371
  • Artikelnr.: 37342240
Autorenporträt
ENRIQUE ALBA, PhD, is a Professor of Computer Science at the University of Málaga, Spain. His research interests involve the design and application of evolutionary algorithms, neural networks, parallelism, and metaheuristic algorithms to solve problems in telecommunications, combinatorial optimization, and bioinformatics. Dr. Alba has published many papers in leading journals and international conferences, and has garnered international awards for his research.
Inhaltsangabe
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.
Rezensionen
"...a good overview of recent metaheuristic techniques, and can be used as a starting point for developing new parallel version of the methods." ( Computing Reviews.com , March 13, 2006)