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Genetic and Evolutionary Computation - GECCO 2004 (häftad)
Format
Häftad (Paperback)
Språk
Engelska
Antal sidor
1442
Utgivningsdatum
2004-10-01
Upplaga
2004 ed.
Förlag
Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Medarbetare
Deb, Kalyanmoy (ed.), Poli, Riccardo (ed.), Banzhaf, Wolfgang (ed.)
Illustrationer
XCVIII, 1442 p. In 2 volumes, not available separately.
Volymtitel
Part II
Antal komponenter
2
Komponenter
2 Paperbacks
ISBN
9783540223436
Genetic and Evolutionary Computation - GECCO 2004 (häftad)

Genetic and Evolutionary Computation - GECCO 2004

Genetic and Evolutionary Computation Conference Seattle, WA, USA, June 26-30, 2004 Proceedings, Part I

Häftad Engelska, 2004-10-01
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MostMOEAsuseadistancemetricorothercrowdingmethodinobjectivespaceinorder to maintain diversity for the non-dominated solutions on the Pareto optimal front. By ensuring diversity among the non-dominated solutions, it is possible to choose from a variety of solutions when attempting to solve a speci?c problem at hand. Supposewehavetwoobjectivefunctionsf (x)andf (x).Inthiscasewecande?ne 1 2 thedistancemetricastheEuclideandistanceinobjectivespacebetweentwoneighboring individuals and we thus obtain a distance given by 2 2 2 d (x ,x )=[f (x )?f (x )] +[f (x )?f (x )] . (1) 1 2 1 1 1 2 2 1 2 2 f wherex andx are two distinct individuals that are neighboring in objective space. If 1 2 2 2 the functions are badly scaled, e.g.[?f (x)] [?f (x)] , the distance metric can be 1 2 approximated to 2 2 d (x ,x )? [f (x )?f (x )] . (2) 1 2 1 1 1 2 f Insomecasesthisapproximationwillresultinanacceptablespreadofsolutionsalong the Pareto front, especially for small gradual slope changes as shown in the illustrated example in Fig. 1. 1.0 0.8 0.6 0.4 0.2 0 0 20 40 60 80 100 f 1 Fig.1.Forfrontswithsmallgradualslopechangesanacceptabledistributioncanbeobtainedeven if one of the objectives (in this casef ) is neglected from the distance calculations. 2 As can be seen in the ?gure, the distances marked by the arrows are not equal, but the solutions can still be seen to cover the front relatively well.
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Innehållsförteckning

Genetic Algorithms (Continued).- PID Controller Tuning for Stable and Unstable Processes Applying GA.- Dynamic Uniform Scaling for Multiobjective Genetic Algorithms.- Parameter-Less Hierarchical BOA.- Computational Complexity and Simulation of Rare Events of Ising Spin Glasses.- Fitness Inheritance in the Bayesian Optimization Algorithm.- Limit Cycle Prediction in Multivariable Nonlinear Systems Using Genetic Algorithms.- Evolving Reusable Neural Modules.- How Are We Doing? Predicting Evolutionary Algorithm Performance.- of a New Selection Parameter in Genetic Algorithm for Constrained Reliability Design Problems.- Improving the Performance of a Genetic Algorithm Using a Variable-Reordering Algorithm.- Designing Competent Mutation Operators Via Probabilistic Model Building of Neighborhoods.- Let's Get Ready to Rumble: Crossover Versus Mutation Head to Head.- Classification with Scaled Genetic Algorithms in a Coevolutionary Setting.- New Epistasis Measures for Detecting Independently Optimizable Partitions of Variables.- Clustering with Niching Genetic K-means Algorithm.- A Comparison of Genetic Programming and Genetic Algorithms in the Design of a Robust, Saturated Control System.- Upper Bounds on the Time and Space Complexity of Optimizing Additively Separable Functions.- Winnowing Wheat from Chaff: The Chunking GA.- An Effective Chromosome Representation for Evolving Flexible Job Shop Schedules.- Linkage Identification by Nonlinearity Check for Real-Coded Genetic Algorithms.- Population-Based Iterated Local Search: Restricting Neighborhood Search by Crossover.- Modeling Dependencies of Loci with String Classification According to Fitness Differences.- The Edge-Set Encoding Revisited: On the Bias of a Direct Representation for Trees.- A Gene Based Adaptive Mutation Strategy for Genetic Algorithms.- Subthreshold-Seeking Behavior and Robust Local Search.- Ruffled by Ridges: How Evolutionary Algorithms Can Fail.- Non-stationary Subtasks Can Improve Diversity in Stationary Tasks.- The Shifting Balance Genetic Algorithm as More than Just Another Island Model GA.- Bistability of the Needle Function in the Presence of Truncation Selection.- An Estimation of Distribution Algorithm Based on Maximum Entropy.- Dependency Structure Matrix Analysis: Offline Utility of the Dependency Structure Matrix Genetic Algorithm.- Toward an Understanding of the Quality and Efficiency of Model Building for Genetic Algorithms.- Genetic Algorithms - Posters.- Sexual and Asexual Paradigms in Evolution: The Implications for Genetic Algorithms.- Mutation Rates in the Context of Hybrid Genetic Algorithms.- Systematic Integration of Parameterized Local Search Techniques in Evolutionary Algorithms.- Comparative Molecular Binding Energy Analysis of HIV-1 Protease Inhibitors Using Genetic Algorithm-Based Partial Least Squares Method.- Controlled Content Crossover: A New Crossover Scheme and Its Application to Optical Network Component Allocation Problem.- Efficient and Reliable Evolutionary Multiobjective Optimization Using ?-Dominance Archiving and Adaptive Population Sizing.- Heuristic Methods for Solving Euclidean Non-uniform Steiner Tree Problems.- Automating Evolutionary Art in the Style of Mondrian.- Mutation Can Improve the Search Capability of Estimation of Distribution Algorithms.- Neural Network Normalization for Genetic Search.- Distance Measures in Genetic Algorithms.- Analysis of a Parallel MOEA Solving the Multi-objective Quadratic Assignment Problem.- Evolving Features in Neural Networks for System Identification.- A Bio-inspired Genetic Algorithm with a Self-Organizing Genome: The RBF-Gene Model.- Evolving Spike-Train Processors.- A Philosophical Essay on Life and Its Connections with Genetic Algorithms.- An Architecture for Massive Parallelization of the Compact Genetic Algorithm.- An Evolutionary Technique for Multicriterial Optimization Based on Endocrine Paradigm.- Evolving Golomb Rulers.- Populating Genomes in a Dynamic Grid.- Empirical Stu