Balıkesir Üniversitesi
Kütüphane ve Dokümantasyon Daire Başkanlığı

Optimization techniques for solving complex problems / (Kayıt no. 25079)

MARC ayrıntıları
000 -LEADER
fixed length control field 08394nam a2200301 i 4500
001 - CONTROL NUMBER
control field 28746
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 101021s2009 njudf b 001 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780470293324
International Standard Book Number 0470293322
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC)
040 ## - CATALOGING SOURCE
Original cataloging agency BAUN
Language of cataloging eng
Transcribing agency BAUN
Description conventions rda
049 ## - LOCAL HOLDINGS (OCLC)
Holding library BAUN_MERKEZ
050 04 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA76.9.M35
Item number O68 2009
245 00 - TITLE STATEMENT
Title Optimization techniques for solving complex problems /
Statement of responsibility, etc editör, Enrique Alba [and others]
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Hoboken, N.J. :
Name of producer, publisher, distributor, manufacturer Wiley,
Date of production, publication, distribution, manufacture, or copyright notice c2009.
300 ## - PHYSICAL DESCRIPTION
Extent xxi, 476 pages :
Other physical details illustrations ;
Dimensions 25 cm.
336 ## - CONTENT TYPE
Source rdacontent
Content Type Term text
Content Type Code txt
337 ## - MEDIA TYPE
Source rdamedia
Media Type Term unmediated
Media Type Code unmediated
338 ## - CARRIER TYPE
Source rdacarrier
Carrier Type Term volume
Carrier Type Code volume
490 0# - SERIES STATEMENT
Series statement Wiley series on parallel and distributed computing.
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Includes bibliographical references and index.
505 00 - FORMATTED CONTENTS NOTE
Title PART I: METHODOLOGIES FOR COMPLEX PROBLEM SOLVING.
-- 1. Generating Automatic Projections by Means of GP (C. Estébanez,and R. Aler).
-- 1.1 Introduction.
-- 1.2 Background.
-- 1.3 Domains.
-- 1.4 Algorithmic Proposal.
-- 1.5 Experimental Analysis.
-- 1.6 Conclusions and Future Work.
-- References.
-- 2. Neural Lazy Local Learning (J. M. Valls, I. M. Galván, and P. Isasi).
-- 2.1 Introduction.
-- 2.2 LRBNN: Lazy Radial Basis Neural Networks.
-- 2.3 Experimental Framework.
-- 2.4 Conclusions.
-- References.
-- 3. Optimization by Using GAs with Micropopulations (Y. Sáez).
-- 3.1 Introduction.
-- 3.2 Algorithmic Proposal.
-- 3.3 Experimental Analysis: the Rastrigin Function.
-- 3.4 Conclusions.
-- References.
-- 4. Analyzing Parallel Cellular Genetic Algorithms (G. Luque, E. Alba, and B. Dorronsoro).
-- 4.1 Introduction.
-- 4.2 Cellular Genetic Algorithms.
-- 4.3 Parallel Models for cGAs.
-- 4.4 Brief Survey on Parallel cGAs.
-- 4.5 Experimental Results.
-- 4.6 Conclusions.
-- References.
-- 5. Evaluating New Advanced Multiobjective Metaheuristics (A. J. Nebro, J.J. Durillo, F. Luna, and E. Alba).
-- 5.1 Introduction.
-- 5.2 Background.
-- 5.3 Description of the Metaheuristics.
-- 5.4 Experimentation Methodology.
-- 5.5 Computational Results.
-- 5.6 Conclusions and Future Work.
-- References.
-- 6. Canonical Metaheuristics for DOPs (G. Leguizamón, G. Ordóñez, S. Molina, and E. Alba).
-- 6.1 Introduction.
-- 6.2 Dynamic Optimization Problems.
-- 6.3 Canonical MHs for DOPs.
-- 6.4 Benchmarks.
-- 6.5 Metrics.
-- 6.6 Conclusions.
-- References.
-- 7. Solving Constrained Optimization Problems with HEAs (C. Cotta, and A. J. Fernández).
-- 7.1 Introduction.
-- 7.2 Strategies for Solving CCOPs with HEAs.
-- 7.3 Study Cases.
-- 7.4 Conclusions.
-- 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).
-- 8.1 Introduction.
-- 8.2 Time Series Identification.
-- 8.3 Optimization Problem.
-- 8.4 Algorithmic Proposal.
-- 8.5 Experimental Analysis.
-- 8.6 Conclusions and Future Work.
-- References.
-- 9. Using Reconfigurable Computing to Optimization of Cryptographic Algorithms (J. M. Granado, M. A. Vega, J. M. Sanchez, and J. A. Gomez).
-- 9.1 Introduction.
-- 9.2 Description of the Cryptographic Algorithms.
-- 9.3 Implementation Proposal.
-- 9.4 Results.
-- 9.5 Conclusions.
-- References.
-- 10. Genetic Algorithms, Parallelism and Reconfigurable Hardware (J. M. Sanchez, M. Rubio, M. A. Vega, and J. A. Gomez).
-- 10.1 Introduction.
-- 10.2 State of the Art.
-- 10.3 FPGA Problem Description and Solution.
-- 10.4 Algorithmic Proposal.
-- 10.5 Experiments and Results.
-- 10.6 Conclusions and Future Work.
-- References.
-- 11. Divide and Conquer, Advanced Techniques (C. Lóon, G. Miranda, and C. Rodriguez).
-- 11.1 Introduction.
-- 11.2 The Algorithm of the Skeleton.
-- 11.3 Computational Results.
-- 11.4 Conclusions.
-- References.
-- 12. Tools for Tree Searches: Branch and Bound and A* Algorithms (C. León, G. Miranda, and C. Rodriguez).
-- 12.1 Introduction.
-- 12.2 Background.
-- 12.3 Algorithmic Skeleton for Tree Searches.
-- 12.4 Experimentation Methodology.
-- 12.5 Computational Results.
-- 12.6 Conclusions and Future Work.
-- References.
-- 13. Tools for Tree Searches: Dynamic Programming (C. León, G. Miranda, and C. Rodriguez).
-- 13.1 Introduction.
-- 13.2 The TopDown.
-- Approach.
-- 13.3 The BottomUp Approach.
-- 13.4 Automata Theory and Dynamic Programming.
-- 13.5 Parallel Algorithms.
-- 13.6 Dynamic Programming Heuristics.
-- 13.7 Conclusions.
-- References.
-- PART II: APPLICATIONS.
-- 14. Automatic Search of Behavior Strategies in Auctions (D. Quintana, and A. Mochón).
-- 14.1 Introduction.
-- 14.2 Evolutionary Techniques in Auctions.
-- 14.3 Theoretical Framework: the Ausubel Auction.
-- 14.4 Algorithmic Proposal.
-- 14.5 Experimental analysis.
-- 14.6 Conclusions and Future Work.
-- References.
-- 15. Evolving Rules For Local Time Series Prediction (C. Luque, J. M. Valls, and P. Isasi).
-- 15.1 Introduction.
-- 15.2 Evolutionary Algorithms for Generating Prediction Rules.
-- 15.3 Description of the Method.
-- 15.4 Experiments.
-- 15.5 Conclusions.
-- References.
-- 16. Metaheuristics in Bioinformatics (C. Cotta, A. J. Fernández, J. E. Gallardo, G. Luque, and E. Alba).
-- 16.1 Introduction.
-- 16.2 Metaheuristics and Bioinformatics.
-- 16.3 The DNA Fragment Assembly Problem.
-- 16.4 The Shortest Common Supersequence Problem.
-- 16.5 Conclusions.
-- References.
-- 17. Optimal Location of Antennae in Telecommunication Networks (G. Molina, F. Chicano, and E. Alba).
-- 17.1 Introduction.
-- 17.2 State of the Art.
-- 17.3 Radio Network Design Problem.
-- 17.4 Optimization Algorithms.
-- 17.5 Basic Problem Instances.
-- 17.6 Advanced Problem Instance.
-- 17.7 Conclusions.
-- References.
-- 18. Optimization of Image Processing Algorithms Using FPGAs (M. A. Vega, A. Gomez, J. A. Gomez, and J. M. Sanchez).
-- 18.1 Introduction.
-- 18.2 Background.
-- 18.3 Main Features of the FPGAbased Image Processing.
-- 18.4 Advanced Details.
-- 18.5 Experimental Analysis: Software vs. FPGA.
-- 18.6 Conclusions.
-- 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).
-- 19.1 Introduction.
-- 19.2 Background.
-- 19.3 The Problem: Laser Dynamics.
-- 19.4 Algorithmic Proposal.
-- 19.5 Experimental Analysis.
-- 19.6 Parallel Implementation of the Algorithm.
-- 19.7 Conclusions and Future Work.
-- References.
-- 20. Dense Stereo Disparity from an ALife Standpoint (G. Olague, F. Fernandez, C. B. Perez, and E. Lutton).
-- 20.1 Introduction.
-- 20.2 Infection Algorithm with an Evolutionary Approach.
-- 20.3 Experimental Results.
-- 20.4 Conclusion.
-- References.
-- 21. Approaches to Multidimensional Knapsack Problems (J. E. Gallardo, C. Cotta, and A. J. Fernández).
-- 21.1 Introduction.
-- 21.2 The Multidimensional Knapsack Problem.
-- 21.3 Hybrid Models.
-- 21.4 Experimental Results.
-- 21.5 Conclusions and Future Work.
-- References.
-- 22. Greedy Seeding and ProblemSpecific Operators for GAs Solving Strip Packing Problems (C. Salto, J. M. Molina, and E. Alba).
-- 22.1 Introduction.
-- 22.2 Background.
-- 22.3 A Hybrid GA for the 2SPP.
-- 22.4 Genetic Operators for Solving the 2SPP.
-- 22.5 Initial Seeding.
-- 22.6 Implementation.
-- 22.7 Computational Analysis.
-- 22.8 Conclusions.
-- References.
-- 23. Solving the KCT Problem: Large Scale Neighborhood Search and Solution Merging (C. Blum, and M. Blesa).
-- 23.1 Introduction.
-- 23.2 Hybrid Algorithms for the KCT Problem.
-- 23.3 Experimental Evaluation.
-- 23.4 Summary and Conclusions.
-- References.
-- 24. Experimental Study of Gabased Schedulers in Dynamic Distributed Computing Environments (F. Xhafa, and J. Carretero).
-- 24.1 Introduction.
-- 24.2 Related Work.
-- 24.3 Independent Job Scheduling Problem.
-- 24.4 Genetic Algorithms for Scheduling in Grid Systems.
-- 24.5 Grid Simulator.
-- 24.6 The Interface for Using Gabased Scheduler with the Grid Simulator.
-- 24.7 Experimental Analysis.
-- 24.8 Conclusions.
-- References.
-- 25. ROS: Remote Optimization Service (J. GarcíaNieto, F. Chicano, and E. Alba).
-- 25.1 Introduction.
-- 25.2 Background and State of the Art.
-- 25.3 ROS Architecture.
-- 25.4 Information Exchange in ROS.
-- 25.5 XML in ROS.
-- 25.6 Wrappers.
-- 25.7 Evaluation of ROS.
-- 25.8 Conclusions and Future Work.
-- 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).
-- 26.1 Introduction.
-- 26.2 SIRVA.
-- 26.3 MOSET and TIDESI.
-- 26.4 ABACUS.
-- References.
-- Index.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer science
General subdivision Mathematics.
Topical term or geographic name as entry element Mathematical optimization.
Topical term or geographic name as entry element Problem solving.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Alba, Enrique.
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Library of Congress Classification
Koha item type Kitap
Mevcut
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Home library Current library Shelving location Date acquired Source of acquisition Cost, normal purchase price Inventory number Full call number Barcode Date last seen Price effective from Koha item type
    Library of Congress Classification     Non-fiction Mehmet Akif Ersoy Merkez Kütüphanesi Mehmet Akif Ersoy Merkez Kütüphanesi Genel Koleksiyon 21/10/2010 Satın Alma 172.44 255.07.02.01.06- QA76.9.M35 O68 2009 028746 22/12/2015 11/01/2015 Kitap
Bizi Sosyal Medyada Takip Edin