000 05565cam a22004334a 4500
999 _c62359
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001 13844392
003 CITU
005 20230217173113.0
007 cr an aaaaa
008 050118s2005 njua b 001 0 eng
010 _a 2005001251
020 _a9780471739371
020 _a9780471739388 (ebooks)
040 _aDLC
_cDLC
_dDLC
_dDLC
041 _aeng.
042 _apcc
050 0 0 _aT57
_b.P37 2005
082 0 0 _a519.6
_222
245 0 0 _aParallel metaheuristics :
_ba new class of algorithms /
_cedited by Enrique Alba.
264 1 _aHoboken, New Jersey :
_b John Wiley & Sons, Inc.,
_c2005.
300 _a1 online resource (565 pages).
336 _2rdacontent
_atext
_btxt
337 _2rdamedia
_acomputer
_bc
338 _2rdacarrier
_aonline resource
_bcr
440 0 _aWiley series on parallel and distributed computing
500 _aABOUT THE AUTHOR 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.
504 _aIncludes bibliographical references and index.
505 0 _aForeword. 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.
520 _aSolving 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.
526 _a500-599
_b519
650 0 _aMathematical optimization.
650 0 _aParallel algorithms.
650 0 _aMetaheuristics.
650 0 _aOperations research.
655 4 _aElectronic books.
700 1 _aAlba, Enrique.
856 _yFull text available at Wiley Online Library Click here to view
_uhttps://onlinelibrary.wiley.com/doi/book/10.1002/0471739383
942 _2ddc
_cER