Genetic and Evolutionary Computation - GECCO 2003 (häftad)
Format
Häftad (Paperback / softback)
Språk
Engelska
Antal sidor
1280
Utgivningsdatum
2003-06-01
Upplaga
2003 ed.
Förlag
Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Medarbetare
Cantù-Paz, E. (ed.), Wilson, S. (ed.), Wegener, J. (ed.)
Illustrationer
818 Illustrations, black and white; XCIV, 1280 p. 818 illus. In 2 volumes, not available separately.
Volymtitel
Pt. 2
Antal komponenter
2
Komponenter
2 Paperback / softbacks
ISBN
9783540406037
Genetic and Evolutionary Computation - GECCO 2003 (häftad)

Genetic and Evolutionary Computation - GECCO 2003

Genetic and Evolutionary Computation Conference Chicago, IL, USA, July 12-16, 2003 Proceedings, Part II

Häftad Engelska, 2003-06-01
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These proceedings contain the papers presented at the 5th Annual Genetic and EvolutionaryComputationConference(GECCO2003).Theconferencewasheld in Chicago, USA, July 12-16, 2003. A total of 417 papers were submitted to GECCO 2003. After a rigorous doubleblind reviewing process, 194 papers were accepted for full publication and oral presentation at the conference, resulting in an acceptance rate of 46.5%. An additional 92 submissions were accepted as posters with two-page extended abstracts included in these proceedings. This edition of GECCO was the union of the 8th Annual Genetic Progr- mingConference(whichhasmetannuallysince1996)andthe12thInternational Conference on Genetic Algorithms (which, with its ?rst meeting in 1985, is the longest running conference in the ?eld). Since 1999, these conferences have m- ged to produce a single large meeting that welcomes an increasingly wide array of topics related to genetic and evolutionary computation. Possibly the most visible innovation in GECCO 2003 was the publication of theproceedingswithSpringer-VerlagaspartoftheirLectureNotesinComputer Science series. This will make the proceedings available in many libraries as well asonline,wideningthedisseminationoftheresearchpresentedattheconference. OtherinnovationsincludedanewtrackonCoevolutionandArti?cialImmune Systems and the expansion of the DNA and Molecular Computing track to include quantum computation. In addition to the presentation of the papers contained in these proceedings, the conference included 13 workshops, 32 tutorials by leading specialists, and presentation of late-breaking papers. GECCO is sponsored by the International Society for Genetic and Evolut- nary Computation (ISGEC). The ISGEC by-laws contain explicit guidance on the organization of the conference, including the following principles: (i)GECCOshouldbeabroad-basedconferenceencompassingthewhole?eld of genetic and evolutionary computation.
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Genetic Algorithms.- Design of Multithreaded Estimation of Distribution Algorithms.- Reinforcement Learning Estimation of Distribution Algorithm.- Hierarchical BOA Solves Ising Spin Glasses and MAXSAT.- ERA: An Algorithm for Reducing the Epistasis of SAT Problems.- Learning a Procedure That Can Solve Hard Bin-Packing Problems: A New GA-Based Approach to Hyper-heuristics.- Population Sizing for the Redundant Trivial Voting Mapping.- Non-stationary Function Optimization Using Polygenic Inheritance.- Scalability of Selectorecombinative Genetic Algorithms for Problems with Tight Linkage.- New Entropy-Based Measures of Gene Significance and Epistasis.- A Survey on Chromosomal Structures and Operators for Exploiting Topological Linkages of Genes.- Cellular Programming and Symmetric Key Cryptography Systems.- Mating Restriction and Niching Pressure: Results from Agents and Implications for General EC.- EC Theory: A Unified Viewpoint.- Real Royal Road Functions for Constant Population Size.- Two Broad Classes of Functions for Which a No Free Lunch Result Does Not Hold.- Dimensionality Reduction via Genetic Value Clustering.- The Structure of Evolutionary Exploration: On Crossover, Buildings Blocks, and Estimation-Of-Distribution Algorithms.- The Virtual Gene Genetic Algorithm.- Quad Search and Hybrid Genetic Algorithms.- Distance between Populations.- The Underlying Similarity of Diversity Measures Used in Evolutionary Computation.- Implicit Parallelism.- Finding Building Blocks through Eigenstructure Adaptation.- A Specialized Island Model and Its Application in Multiobjective Optimization.- Adaptation of Length in a Nonstationary Environment.- Optimal Sampling and Speed-Up for Genetic Algorithms on the Sampled OneMax Problem.- Building-Block Identification by Simultaneity Matrix.- A Unified Framework for Metaheuristics.- The Hitting Set Problem and Evolutionary Algorithmic Techniques with ad-hoc Viruses (HEAT-V).- The Spatially-Dispersed Genetic Algorithm.- Non-universal Suffrage Selection Operators Favor Population Diversity in Genetic Algorithms.- Uniform Crossover Revisited: Maximum Disruption in Real-Coded GAs.- The Master-Slave Architecture for Evolutionary Computations Revisited.- Genetic Algorithms - Posters.- Using Adaptive Operators in Genetic Search.- A Kernighan-Lin Local Improvement Heuristic That Solves Some Hard Problems in Genetic Algorithms.- GA-Hardness Revisited.- Barrier Trees For Search Analysis.- A Genetic Algorithm as a Learning Method Based on Geometric Representations.- Solving Mastermind Using Genetic Algorithms.- Evolutionary Multimodal Optimization Revisited.- Integrated Genetic Algorithm with Hill Climbing for Bandwidth Minimization Problem.- A Fixed-Length Subset Genetic Algorithm for the p-Median Problem.- Performance Evaluation of a Parameter-Free Genetic Algorithm for Job-Shop Scheduling Problems.- SEPA: Structure Evolution and Parameter Adaptation in Feed-Forward Neural Networks.- Real-Coded Genetic Algorithm to Reveal Biological Significant Sites of Remotely Homologous Proteins.- Understanding EA Dynamics via Population Fitness Distributions.- Evolutionary Feature Space Transformation Using Type-Restricted Generators.- On the Locality of Representations.- New Subtour-Based Crossover Operator for the TSP.- Is a Self-Adaptive Pareto Approach Beneficial for Controlling Embodied Virtual Robots?.- A Genetic Algorithm for Energy Efficient Device Scheduling in Real-Time Systems.- Metropolitan Area Network Design Using GA Based on Hierarchical Linkage Identification.- Statistics-Based Adaptive Non-uniform Mutation for Genetic Algorithms.- Genetic Algorithm Design Inspired by Organizational Theory: Pilot Study of a Dependency Structure Matrix Driven Genetic Algorithm.- Are the "Best" Solutions to a Real Optimization Problem Always Found in the Noninferior Set? Evolutionary Algorithm for Generating Alternatives (EAGA).- Population Sizing Based on Landscape Feature.- Genetic Programming.- Structural