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PART II: APPLICATIONS
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PART II: APPLICATIONS
by Juan Antonio Gomez, Coromoto Leon, Pedro Asasi, Christian Blum, Enrique Alba
Optimization Techniques for Solving Complex Problems
Cover Page
WILEY SERIES ON PARALLEL AND DISTRIBUTED COMPUTING
Title Page
Copyright
Dedication
CONTENTS
CONTRIBUTORS
FOREWORD
PREFACE
PART I: METHODOLOGIES FOR COMPLEX PROBLEM SOLVING
CHAPTER 1: Generating Automatic Projections by Means of Genetic Programming
1.1 INTRODUCTION
1.2 BACKGROUND
1.3 DOMAINS
1.4 ALGORITHMIC PROPOSAL
1.5 EXPERIMENTAL ANALYSIS
1.6 CONCLUSIONS
REFERENCES
CHAPTER 2: Neural Lazy Local Learning
2.1 INTRODUCTION
2.2 LAZY RADIAL BASIS NEURAL NETWORKS
2.3 EXPERIMENTAL ANALYSIS
2.4 CONCLUSIONS
REFERENCES
CHAPTER 3: Optimization Using Genetic Algorithms with Micropopulations
3.1 INTRODUCTION
3.2 ALGORITHMIC PROPOSAL
3.3 EXPERIMENTAL ANALYSIS: THE RASTRIGIN FUNCTION
3.4 CONCLUSIONS
REFERENCES
CHAPTER 4: Analyzing Parallel Cellular Genetic Algorithms
4.1 INTRODUCTION
4.2 CELLULAR GENETIC ALGORITHMS
4.3 PARALLEL MODELS FOR cGAs
4.4 BRIEF SURVEY OF PARALLEL cGAs
4.5 EXPERIMENTAL ANALYSIS
4.6 CONCLUSIONS
REFERENCES
CHAPTER 5: Evaluating New Advanced Multiobjective Metaheuristics
5.1 INTRODUCTION
5.2 BACKGROUND
5.3 DESCRIPTION OF THE METAHEURISTICS
5.4 EXPERIMENTAL METHODOLOGY
5.5 EXPERIMENTAL ANALYSIS
5.6 CONCLUSIONS
REFERENCES
CHAPTER 6: Canonical Metaheuristics for Dynamic Optimization Problems
6.1 INTRODUCTION
6.2 DYNAMIC OPTIMIZATION PROBLEMS
6.3 CANONICAL MHs FOR DOPs
6.4 BENCHMARKS
6.5 METRICS
6.6 CONCLUSIONS
REFERENCES
CHAPTER 7: Solving Constrained Optimization Problems with Hybrid Evolutionary Algorithms
7.1 INTRODUCTION
7.2 STRATEGIES FOR SOLVING CCOPs WITH HEAs
7.3 STUDY CASES
7.4 CONCLUSIONS
REFERENCES
CHAPTER 8: Optimization of Time Series Using Parallel, Adaptive, and Neural Techniques
8.1 INTRODUCTION
8.2 TIME SERIES IDENTIFICATION
8.3 OPTIMIZATION PROBLEM
8.4 ALGORITHMIC PROPOSAL
8.5 EXPERIMENTAL ANALYSIS
8.6 CONCLUSIONS
REFERENCES
CHAPTER 9: Using Reconfigurable Computing for the Optimization of Cryptographic Algorithms
9.1 INTRODUCTION
9.2 DESCRIPTION OF THE CRYPTOGRAPHIC ALGORITHMS
9.3 IMPLEMENTATION PROPOSAL
9.4 EXPERMENTAL ANALYSIS
9.5 CONCLUSIONS
REFERENCES
CHAPTER 10: Genetic Algorithms, Parallelism, and Reconfigurable Hardware
10.1 INTRODUCTION
10.2 STATE OF THE ART
10.3 FPGA PROBLEM DESCRIPTION AND SOLUTION
10.4 ALGORITHMIC PROPOSAL
10.5 EXPERIMENTAL ANALYSIS
10.6 CONCLUSIONS
REFERENCES
CHAPTER 11: Divide and Conquer: Advanced Techniques
11.1 INTRODUCTION
11.2 ALGORITHM OF THE SKELETON
11.3 EXPERIMENTAL ANALYSIS
11.4 CONCLUSIONS
REFERENCES
CHAPTER 12: Tools for Tree Searches: Branch-and-Bound and A* Algorithms
12.1 INTRODUCTION
12.2 BACKGROUND
12.3 ALGORITHMIC SKELETON FOR TREE SEARCHES
12.4 EXPERIMENTATION METHODOLOGY
12.5 EXPERIMENTAL RESULTS
12.6 CONCLUSIONS
REFERENCES
CHAPTER 13: Tools for Tree Searches: Dynamic Programming
13.1 INTRODUCTION
13.2 TOP-DOWN APPROACH
13.3 BOTTOM-UP APPROACH
13.4 AUTOMATA THEORY AND DYNAMIC PROGRAMMING
13.5 PARALLEL ALGORITHMS
13.6 DYNAMIC PROGRAMMING HEURISTICS
13.7 CONCLUSIONS
REFERENCES
PART II: APPLICATIONS
CHAPTER 14: Automatic Search of Behavior Strategies in Auctions
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
REFERENCES
CHAPTER 15: Evolving Rules for Local Time Series Prediction
15.1 INTRODUCTION
15.2 EVOLUTIONARY ALGORITHMS FOR GENERATING PREDICTION RULES
15.3 EXPERIMENTAL METHODOLOGY
15.4 EXPERIMENTS
15.5 CONCLUSIONS
REFERENCES
CHAPTER 16: Metaheuristics in Bioinformatics: DNA Sequencing and Reconstruction
16.1 INTRODUCTION
16.2 METAHEURISTICS AND BIOINFORMATICS
16.3 DNA FRAGMENT ASSEMBLY PROBLEM
16.4 SHORTEST COMMON SUPERSEQUENCE PROBLEM
16.5 CONCLUSIONS
REFERENCES
CHAPTER 17: Optimal Location of Antennas in Telecommunication Networks
17.1 INTRODUCTION
17.2 STATE OF THE ART
17.3 RADIO NETWORK DESIGN PROBLEM
17.4 OPTIMIZATION ALGORITHMS
17.5 BASIC PROBLEMS
17.6 ADVANCED PROBLEM
17.7 CONCLUSIONS
REFERENCES
CHAPTER 18: Optimization of Image-Processing Algorithms Using FPGAs
18.1 INTRODUCTION
18.2 BACKGROUND
18.3 MAIN FEATURES OF FPGA-BASED IMAGE PROCESSING
18.4 ADVANCED DETAILS
18.5 EXPERIMENTAL ANALYSIS: SOFTWARE VERSUS FPGA
18.6 CONCLUSIONS
REFERENCES
CHAPTER 19: Application of Cellular Automata Algorithms to the Parallel Simulation of Laser Dynamics
19.1 INTRODUCTION
19.2 BACKGROUND
19.3 LASER DYNAMICS PROBLEM
19.4 ALGORITHMIC PROPOSAL
19.5 EXPERIMENTAL ANALYSIS
19.6 PARALLEL IMPLEMENTATION OF THE ALGORITHM
19.7 CONCLUSIONS
REFERENCES
CHAPTER 20: Dense Stereo Disparity from an Artificial Life Standpoint
20.1 INTRODUCTION
20.2 INFECTION ALGORITHM WITH AN EVOLUTIONARY APPROACH
20.3 EXPERIMENTAL ANALYSIS
20.4 CONCLUSIONS
REFERENCES
CHAPTER 21: Exact, Metaheuristic, and Hybrid Approaches to Multidimensional Knapsack Problems
21.1 INTRODUCTION
21.2 MULTIDIMENSIONAL KNAPSACK PROBLEM
21.3 HYBRID MODELS
21.4 EXPERIMENTAL ANALYSIS
21.5 CONCLUSIONS
REFERENCES
CHAPTER 22: Greedy Seeding and Problem-Specific Operators for GAs Solution of Strip Packing Problems
22.1 INTRODUCTION
22.2 BACKGROUND
22.3 HYBRID GA FOR THE 2SPP
22.4 GENETIC OPERATORS FOR SOLVING THE 2SPP
22.5 INITIAL SEEDING
22.6 IMPLEMENTATION OF THE ALGORITHMS
22.7 EXPERIMENTAL ANALYSIS
22.8 CONCLUSIONS
REFERENCES
CHAPTER 23: Solving the KCT Problem: Large-Scale Neighborhood Search and Solution Merging
23.1 INTRODUCTION
23.2 HYBRID ALGORITHMS FOR THE KCT PROBLEM
23.3 EXPERIMENTAL ANALYSIS
23.4 CONCLUSIONS
REFERENCES
CHAPTER 24: Experimental Study of GA-Based Schedulers in Dynamic Distributed Computing Environments
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 INTERFACE FOR USING A GA-BASED SCHEDULER WITH THE GRID SIMULATOR
24.7 EXPERIMENTAL ANALYSIS
24.8 CONCLUSIONS
REFERENCES
CHAPTER 25: Remote Optimization Service
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
REFERENCES
CHAPTER 26: Remote Services for Advanced Problem Optimization
26.1 INTRODUCTION
26.2 SIRVA
26.3 MOSET AND TIDESI
26.4 ABACUS
REFERENCES
INDEX
WILEY SERIES ON PARALLEL AND DISTRIBUTED COMPUTING Series Editor: Albert Y. Zomaya
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CHAPTER 13: Tools for Tree Searches: Dynamic Programming
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CHAPTER 14: Automatic Search of Behavior Strategies in Auctions
PART II
APPLICATIONS
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