Real world problems and modern optimization techniques to solve them Here, a team of international experts brings together core ideas for solving complex problems in optimization across a wide variety of real world settings, including computer science, engineering, transportation, telecommunications, and bioinformatics. Part One covers methodologies for complex problem solving including genetic programming, neural networks, genetic algorithms, hybrid evolutionary algorithms, and more. Part Two delves into applications including DNA sequencing and reconstruction, location of antennae in…mehr
Real world problems and modern optimization techniques to solve them Here, a team of international experts brings together core ideas for solving complex problems in optimization across a wide variety of real world settings, including computer science, engineering, transportation, telecommunications, and bioinformatics. Part One covers methodologies for complex problem solving including genetic programming, neural networks, genetic algorithms, hybrid evolutionary algorithms, and more. Part Two delves into applications including DNA sequencing and reconstruction, location of antennae in telecommunication networks, metaheuristics, FPGAs, problems arising in telecommunication networks, image processing, time series prediction, and more. All chapters contain examples that illustrate the applications themselves as well as the actual performance of the algorithms.?Optimization Techniques for Solving Complex Problems is a valuable resource for practitioners and researchers who work with optimization in real world settings.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Produktdetails
Produktdetails
The Wiley Series on Parallel and Distributed Computing
Enrique Alba is a Professor of Data Communications and Evolutionary Algorithms at the University of Mßlaga, Spain. Christian Blum is a Research Fellow at the ALBCOM research group of the Universitat PolitÞcnica de Catalunya, Spain. Pedro Isasi?is a Professor of Artificial Intelligence at the University Carlos III of Madrid, Spain. Coromoto Le3/4n is a Professor of Language Processors and Distributed Programming at the University of La Laguna, Spain. Juan Antonio?G3/4mez is a Professor of Computer Architecture and Reconfigurable Computing at the University of Extremadura, Spain.
Inhaltsangabe
PART I: METHODOLOGIES FOR COMPLEX PROBLEM SOLVING. 1. Generating Automatic Projections by Means of GP (C. Estébanez and R. Aler). References. 2. Neural Lazy Local Learning (J. M. Valls I. M. Galván and P. Isasi). References. 3. Optimization by Using GAs with Micropopulations (Y. Sáez). References. 4. Analyzing Parallel Cellular Genetic Algorithms (G. Luque E. Alba and B. Dorronsoro). References. 5. Evaluating New Advanced Multiobjective Metaheuristics (A. J. Nebro J.J. Durillo F. Luna and E. Alba). References. 6. Canonical Metaheuristics for DOPs (G. Leguizamón G. Ordóñez S. Molina and E. Alba). References. 7. Solving Constrained Optimization Problems with HEAs (C. Cotta and A. J. Fernández). References. 8. Optimization of Time Series Using Parallel Adaptive and Neural Techniques (J. A. Gomez M. D. Jaraiz M. A. Vega and J. M. Sanchez). References. 9. Using Reconfigurable Computing to Optimization of Cryptographic Algorithms (J. M. Granado M. A. Vega J. M. Sanchez and J. A. Gomez). References. 10. Genetic Algorithms Parallelism and Reconfigurable Hardware (J. M. Sanchez M. Rubio M. A. Vega and J. A. Gomez). References. 11. Divide and Conquer Advanced Techniques (C. Lóon G. Miranda and C. Rodriguez). References. 12. Tools for Tree Searches: Branch and Bound and A* Algorithms (C. León G. Miranda and C. Rodriguez). References. 13. Tools for Tree Searches: Dynamic Programming (C. León G. Miranda and C. Rodriguez). Approach. References. PART II: APPLICATIONS. 14. Automatic Search of Behavior Strategies in Auctions (D. Quintana and A. Mochón). References. 15. Evolving Rules For Local Time Series Prediction (C. Luque J. M. Valls and P. Isasi). References. 16. Metaheuristics in Bioinformatics (C. Cotta A. J. Fernández J. E. Gallardo G. Luque and E. Alba). References. 17. Optimal Location of Antennae in Telecommunication Networks (G. Molina F. Chicano and E. Alba). References. 18. Optimization of Image Processing Algorithms Using FPGAs (M. A. Vega A. Gomez J. A. Gomez and J. M. Sanchez). References. 19. Application of Cellular Automata Algorithms to the Parallel Simulation of Laser Dynamics (J. L. Guisado F. Jiménez Morales J. M. Guerra F. Fernández de Vega). References. 20. Dense Stereo Disparity from an ALife Standpoint (G. Olague F. Fernandez C. B. Perez and E. Lutton). References. 21. Approaches to Multidimensional Knapsack Problems (J. E. Gallardo C. Cotta and A. J. Fernández). References. 22. Greedy Seeding and ProblemSpecific Operators for GAs Solving Strip Packing Problems (C. Salto J. M. Molina and E. Alba). References. 23. Solving the KCT Problem: Large Scale Neighborhood Search and Solution Merging (C. Blum and M. Blesa). References. 24. Experimental Study of Gabased Schedulers in Dynamic Distributed Computing Environments (F. Xhafa and J. Carretero). References. 25. ROS: Remote Optimization Service (J. GarcíaNieto F. Chicano and E. Alba). References. 26. SIRVA MOSET TIDESI ABACUS: Remote Services for Advanced. Problem Optimization (J. A. Gomez M. A. Vega J. M. Sanchez J. L. Guisado D. Lombrana and F. Fernandez). References. Index.
PART I: METHODOLOGIES FOR COMPLEX PROBLEM SOLVING. 1. Generating Automatic Projections by Means of GP (C. Estébanez and R. Aler). References. 2. Neural Lazy Local Learning (J. M. Valls I. M. Galván and P. Isasi). References. 3. Optimization by Using GAs with Micropopulations (Y. Sáez). References. 4. Analyzing Parallel Cellular Genetic Algorithms (G. Luque E. Alba and B. Dorronsoro). References. 5. Evaluating New Advanced Multiobjective Metaheuristics (A. J. Nebro J.J. Durillo F. Luna and E. Alba). References. 6. Canonical Metaheuristics for DOPs (G. Leguizamón G. Ordóñez S. Molina and E. Alba). References. 7. Solving Constrained Optimization Problems with HEAs (C. Cotta and A. J. Fernández). References. 8. Optimization of Time Series Using Parallel Adaptive and Neural Techniques (J. A. Gomez M. D. Jaraiz M. A. Vega and J. M. Sanchez). References. 9. Using Reconfigurable Computing to Optimization of Cryptographic Algorithms (J. M. Granado M. A. Vega J. M. Sanchez and J. A. Gomez). References. 10. Genetic Algorithms Parallelism and Reconfigurable Hardware (J. M. Sanchez M. Rubio M. A. Vega and J. A. Gomez). References. 11. Divide and Conquer Advanced Techniques (C. Lóon G. Miranda and C. Rodriguez). References. 12. Tools for Tree Searches: Branch and Bound and A* Algorithms (C. León G. Miranda and C. Rodriguez). References. 13. Tools for Tree Searches: Dynamic Programming (C. León G. Miranda and C. Rodriguez). Approach. References. PART II: APPLICATIONS. 14. Automatic Search of Behavior Strategies in Auctions (D. Quintana and A. Mochón). References. 15. Evolving Rules For Local Time Series Prediction (C. Luque J. M. Valls and P. Isasi). References. 16. Metaheuristics in Bioinformatics (C. Cotta A. J. Fernández J. E. Gallardo G. Luque and E. Alba). References. 17. Optimal Location of Antennae in Telecommunication Networks (G. Molina F. Chicano and E. Alba). References. 18. Optimization of Image Processing Algorithms Using FPGAs (M. A. Vega A. Gomez J. A. Gomez and J. M. Sanchez). References. 19. Application of Cellular Automata Algorithms to the Parallel Simulation of Laser Dynamics (J. L. Guisado F. Jiménez Morales J. M. Guerra F. Fernández de Vega). References. 20. Dense Stereo Disparity from an ALife Standpoint (G. Olague F. Fernandez C. B. Perez and E. Lutton). References. 21. Approaches to Multidimensional Knapsack Problems (J. E. Gallardo C. Cotta and A. J. Fernández). References. 22. Greedy Seeding and ProblemSpecific Operators for GAs Solving Strip Packing Problems (C. Salto J. M. Molina and E. Alba). References. 23. Solving the KCT Problem: Large Scale Neighborhood Search and Solution Merging (C. Blum and M. Blesa). References. 24. Experimental Study of Gabased Schedulers in Dynamic Distributed Computing Environments (F. Xhafa and J. Carretero). References. 25. ROS: Remote Optimization Service (J. GarcíaNieto F. Chicano and E. Alba). References. 26. SIRVA MOSET TIDESI ABACUS: Remote Services for Advanced. Problem Optimization (J. A. Gomez M. A. Vega J. M. Sanchez J. L. Guisado D. Lombrana and F. Fernandez). References. Index.
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