
Optimization Techniques for Solving Complex Problems
Wiley (Publisher)
Published on 9. April 2009
Book
Hardback
476 pages
978-0-470-29332-4 (ISBN)
Description
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.
More details
Product info
gebunden
Series
Edition
1. Auflage
Language
English
Place of publication
New York
United States
Target group
College/higher education
Product notice
sewn/stitched
Cloth over boards
Dimensions
Height: 240 mm
Width: 161 mm
Thickness: 31 mm
Weight
915 gr
ISBN-13
978-0-470-29332-4 (9780470293324)
Schweitzer Classification
Other editions
Additional editions

Enrique Alba | Christian Blum | Pedro Asasi
Optimization Techniques for Solving Complex Problems
E-Book
02/2009
Wiley
€147.99
Available for download
Persons
Enrique Alba is a Professor of Data Communications and Evolutionary Algorithms at the University of Málaga, Spain. Christian Blum is a Research Fellow at the ALBCOM research group of the Universitat Politècnica de Catalunya, Spain.
Pedro Isasi?is a Professor of Artificial Intelligence at the University Carlos III of Madrid, Spain. Coromoto León is a Professor of Language Processors and Distributed Programming at the University of La Laguna, Spain. Juan Antonio?Gómez is a Professor of Computer Architecture and Reconfigurable Computing at the University of Extremadura, Spain.
Editor
University of Malaga, Spain
Universitat Politecnica de Catalunya, Spain
Content
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.