ENGLISH

Parallel Metaheuristics: A New Class of Algorithms

Book information

Year
2005
ISBN
9780471678069, 9780471739388
DOI
10.1002/0471739383
Language
english
Format
PDF
Filesize
28 MB (29660463 bytes)
Pages
561\561
Orientation
yes
Scanned
yes
Time added
2013-08-01 04:00:00

Description

Solving complex optimization problems with parallel metaheuristics Parallel Metaheuristics brings together an international group of experts in parallelism and metaheuristics to provide a much-needed synthesis of these two fields. Readers discover how metaheuristic techniques can provide useful and practical solutions for a wide range of problems and application domains, with an emphasis on the fields of telecommunications and bioinformatics. This volume fills a long-existing gap, allowing researchers and practitioners to develop 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, Measuring the Performance of Parallel Metaheuristics, New Technologies in Parallelism, and a head-to-head discussion on Metaheuristics and Parallelism * Part Two: Parallel Metaheuristic Models, including Parallel Genetic Algorithms, Parallel Genetic Programming, Parallel Evolution Strategies, Parallel Ant Colony Algorithms, Parallel Estimation of Distribution Algorithms, Parallel Scatter Search, Parallel Variable Neighborhood Search, Parallel Simulated Annealing, Parallel Tabu Search, Parallel GRASP, Parallel Hybrid Metaheuristics, Parallel Multi-Objective Optimization, and Parallel Heterogeneous Metaheuristics * Part Three: Theory and Applications, including Theory of Parallel Genetic Algorithms, Parallel Metaheuristics Applications, Parallel Metaheuristics in Telecommunications, and a final chapter on Bioinformatics and Parallel Metaheuristics Each self-contained chapter begins with clear overviews and introductions that bring the reader up to speed, describes basic techniques, and ends with a reference list for further study. Packed with numerous tables and figures to illustrate the complex theory and processes, this comprehensive volume also includes numerous practical real-world optimization problems and their solutions. This is essential reading for students and researchers in computer science, mathematics, and engineering who deal with parallelism, metaheuristics, and optimization in general.Content: Chapter 1 An Introduction to Metaheuristic Techniques (pages 1–42): Christian Blum, Andrea Roli and Enrique AlbaChapter 2 Measuring the Performance of Parallel Metaheuristics (pages 43–62): Enrique Alba and Gabriel LuqueChapter 3 New Technologies in Parallelism (pages 63–78): Enrique Alba and Antonio J. NebroChapter 4 Metaheuristics and Parallelism (pages 79–103): E. Alba, E?G. Talbi, G. Luque and N. MelabChapter 5 Parallel Genetic Algorithms (pages 105–125): Gabriel Luque, Enrique Alba and Bernabe DorronsoroChapter 6 Parallel Genetic Programming (pages 127–153): Francisco Fernandez, Giandomenico Spezzano, Marco Tomassini and Leonardo VanneschiChapter 7 Parallel Evolution Strategies (pages 155–169): Gunter RudolphChapter 8 Parallel Ant Colony Algorithms (pages 171–201): Stefan Janson, Daniel Merkle and Martin MiddendorfChapter 9 Parallel Estimation of Distribution Algorithms (pages 203–222): Julio Madera, Enrique Alba and Alberto OchoaChapter 10 Parallel Scatter Search (pages 223–246): Felix Garcia Lopez, Miguel Garcia Torres, Belen Melian Batista, Jose A. Moreno Perez and J. Marcos Moreno VegaChapter 11 Parallel Variable Neighborhood Search (pages 247–266): Jose A. Moreno Perez, Pierre Hansen and Nenad MladenovicChapter 12 Parallel Simulated Annealing (pages 267–287): M. Emin Aydin and Vecihi Yig?itChapter 13 Parallel Tabu Search (pages 289–313): Teodor Gabriel Crainic, Michel Gendreau and Jean? Yves PotvinChapter 14 Parallel Greedy Randomized Adaptive Search Procedures (pages 315–346): Mauricio G.C. Resende and Celso C. RibeiroChapter 15 Parallel Hybrid Metaheuristics (pages 347–370): Carlos Cotta, El?Ghazali Talbi and Enrique AlbaChapter 16 Parallel Multiobjective Optimization (pages 371–394): A.J. Nebro, F. Luna, E.?G. Talbi and E. AlbaChapter 17 Parallel Heterogeneous Metaheuristics (pages 395–422): Francisco Luna, Enrique Alba and Antonio J. NebroChapter 18 Theory of Parallel Genetic Algorithms (pages 423–445): Erick Cantu?PazChapter 19 Parallel Metaheuristics Applications (pages 447–494): Teodor Gabriel Crainic and Nourredine HailChapter 20 Parallel Metaheuristics in Telecommunications (pages 495–515): Sergio Nesmachnow, Hector Cancela, Enrique Alba and Francisco ChicanoChapter 21 Bioinformatics and Parallel Metaheuristics (pages 517–549): Oswaldo Trelles and Andres Rodr?iguez

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