Riassunto
We are proud to introduce the proceedings of the Seventh International C- ference on Parallel Problem Solving from Nature, PPSN VII, held in Granada, Spain, on 7 11 September 2002. PPSN VII was organized back-to-back with the Foundations of Genetic Algorithms (FOGA) conference, which took place in Torremolinos, Malaga, Spain, in the preceding week. ThePPSNseriesofconferencesstartedinDortmund,Germany[1].Fromthat pioneering meeting, the event has been held biennially, in Brussels, Belgium [2], Jerusalem, Israel [3], Berlin, Germany [4], Amsterdam, The Netherlands [5], and Paris, France [6]. During the Paris conference, several bids to host PPSN 2002 were put forward; it was decided that the conference would be held in Granada with Juan J. Merelo Guerv´ os as General Chairman. The scienti?c content of the PPSN conference focuses on problem-solving paradigms gleaned from natural models, with an obvious emphasis on those that display an innate parallelism, such as evolutionary algorithms and ant-colony optimization algorithms. The majority of the papers, however, concentrate on evolutionary and hybrid algorithms, as is shown in the contents of this book and itspredecessors.Thiseditionoftheconferenceproceedingshasalargesectionon applications,betheytoclassicalproblemsortoreal-worldengineeringproblems, which shows how bioinspired algorithms are extending their use in the realms of business and enterprise.
Contenuti
Evolutionary Algorithms Theory.- Random Dynamics Optimum Tracking with Evolution Strategies.- On the Behavior of Evolutionary Global-Local Hybrids with Dynamic Fitness Functions.- Measuring the Searched Space to Guide Efficiency: The Principle and Evidence on Constraint Satisfaction.- On the Analysis of Dynamic Restart Strategies for Evolutionary Algorithms.- Running Time Analysis of Multi-objective Evolutionary Algorithms on a Simple Discrete Optimization Problem.- Fitness Landscapes Based on Sorting and Shortest Paths Problems.- Performance Measures for Dynamic Environments.- Representation/Codification Issues.- Direct Representation and Variation Operators for the Fixed Charge Transportation Problem.- On the Utility of Redundant Encodings in Mutation-Based Evolutionary Search.- Binary Representations of Integers and the Performance of Selectorecombinative Genetic Algorithms.- Variation Operators: Analysis, New Techniques.- Parallel Varying Mutation in Deterministic and Self-adaptive GAs.- Self-organizing Maps for Pareto Optimization of Airfoils.- On Fitness Distributions and Expected Fitness Gain of Mutation Rates in Parallel Evolutionary Algorithms.- Opposites Attract: Complementary Phenotype Selection for Crossover in Genetic Programming.- Theoretical Analysis of the Confidence Interval Based Crossover for Real-Coded Genetic Algorithms.- Deterministic Multi-step Crossover Fusion: A Handy Crossover Composition for GAs.- Operator Learning for a Problem Class in a Distributed Peer-to-Peer Environment.- Crossover Operator Effect in Function Optimization with Constraints.- Reducing Random Fluctuations in Mutative Self-adaptation.- On Weight-Biased Mutation for Graph Problems.- Self-adaptive Operator Scheduling Using the Religion-Based EA.- Probabilistic Model-Building Genetic Algorithms in Permutation Representation Domain Using Edge Histogram.- From Syntactical to Semantical Mutation Operators for Structure Optimization.- Evolutionary Techniques: Coevolution.- Parameter Control within a Co-operative Co-evolutionary Genetic Algorithm.- The Effects of Representational Bias on Collaboration Methods in Cooperative Coevolution.- Multiobjective Optimization.- Parallel and Hybrid Models for Multi-objective Optimization: Application to the Vehicle Routing Problem.- Multiobjective Design Optimization of Merging Configuration for an Exhaust Manifold of a Car Engine.- Multi-objective Co-operative Co-evolutionary Genetic Algorithm.- Bayesian Optimization Algorithms for Multi-objective Optimization.- An Evolutionary Algorithm for Controlling Chaos: The Use of Multi—objective Fitness Functions.- Evolutionary Algorithms: New Techniques.- On Modelling Evolutionary Algorithm Implementations through Co-operating Populations.- Permutation Optimization by Iterated Estimation of Random Keys Marginal Product Factorizations.- Advanced Population Diversity Measures in Genetic Programming.- Introducing Start Expression Genes to the Linkage Learning Genetic Algorithm.- Metamodel—Assisted Evolution Strategies.- Limiting the Number of Fitness Cases in Genetic Programming Using Statistics.- Resource-Based Fitness Sharing.- Evolution Strategy with Neighborhood Attraction Using a Neural Gas Approach.- A New Asynchronous Parallel Evolutionary Algorithm for Function Optimization.- Fighting Bloat with Nonparametric Parsimony Pressure.- Increasing the Serial and the Parallel Performance of the CMA-Evolution Strategy with Large Populations.- Adaptive Reservoir Genetic Algorithm with On-Line Decision Making.- Genetic Algorithm Visualization Using Self-organizing Maps.- Generalised Regression GA for Handling Inseparable Function Interaction: Algorithm and Applications.- Diversity-Guided Evolutionary Algorithms.- Hybrid Algorithms:Neurogenetic Algorithms, Evolutionary Techniques Applied to Neural Nets.- Evolutionary Optimization of Heterogeneous Problems.- Automatic Recurrent and Feed-Forward ANN Rule and Expression Extraction with Genetic Programming.- Learning and Evolution by Minimization of Mutual Information.- Evolved RBF Networks for Time-Series Forecasting and Function Approximation.- Hybrid Algorithms: Memetic, Other.- Evolutive Identification of Fuzzy Systems for Time-Series Prediction.- HyGLEAM–An Approach to Generally Applicable Hybridization of Evolutionary Algorithms.- Co-evolving Memetic Algorithms: Initial Investigations.- Learning Classifier Systems.- Consideration of Multiple Objectives in Neural Learning Classifier Systems.- On Using Constructivism in Neural Classifier Systems.- Initial Modifications to XCS for Use in Interactive Evolutionary Design.- First Results from Experiments in Fuzzy Classifier System Architectures for Mobile Robotics.- TCS Learning Classifier System Controller on a Real Robot.- Comparison of Different Techniques.- Comparing Synchronous and Asynchronous Cellular Genetic Algorithms.- Satellite Range Scheduling: A Comparison of Genetic, Heuristic and Local Search.- The LifeCycle Model: Combining Particle Swarm Optimisation, Genetic Algorithms and HillClimbers.- Metaheuristics for Group Shop Scheduling.- Experimental Investigation of Three Distributed Genetic Programming Models.- Model-Based Search for Combinatorial Optimization: A Comparative Study.- Evolutionary Algorithm Implementations.- A Framework for Distributed Evolutionary Algorithms.- Optimisation of Multilayer Perceptrons Using a Distributed Evolutionary Algorithm with SOAP.- Applications.- Off-Line Evolution of Behaviour for Autonomous Agents in Real-Time Computer Games.- A Parallel Evolutionary Algorithm for Stochastic Natural Language Parsing.- Evolutionary Learning of Boolean Queries by Multiobjective Genetic Programming.- Inferring Phylogenetic Trees Using Evolutionary Algorithms.- Towards a More E.cient Evolutionary Induction of Bayesian Networks.- Robust Multiscale A.ne 2D-Image Registration through Evolutionary Strategies.- Synthesizing Graphical Models Employing Explaining Away.- Constructive Geometric Constraint Solving: A New Application of Genetic Algorithms.- Multimeme Algorithms for Protein Structure Prediction.- A Dynamic Traffic Model for Frequency Assignment.- A Parameter-Free Genetic Algorithm for a Fixed Channel Assignment Problem with Limited Bandwidth.- Real-Coded Parameter-Free Genetic Algorithm for Job-Shop Scheduling Problems.- Clustering Gene Expression Profiles with Memetic Algorithms.- Cellular Automata and Genetic Algorithms for Parallel Problem Solving in Human Genetics.- Evolutionary Graph Generation System and Its Application to Bit-Serial Arithmetic Circuit Synthesis.- Evaluating Multi-criteria Evolutionary Algorithms for Airfoil Optimisation.- Hyperheuristics: A Robust Optimisation Method Applied to Nurse Scheduling.- Evolving the Topology of Hidden Markov Models Using Evolutionary Algorithms.- Solving a Real World Routing Problem Using Multiple Evolutionary Agents.- Other Bioinspired Algorithms: Cellular Automata,Ant Colony Optimization.- An Ant Colony Optimization Approach to the Probabilistic Traveling Salesman Problem.- When Model Bias Is Stronger than Selection Pressure.- Evolution of Asynchronous Cellular Automata.- Improved Ant-Based Clustering and Sorting in a Document Retrieval Interface.- An Adaptive Flocking Algorithm for Spatial Clustering.- Evolution of Asynchronous Cellular Automata for the Density Task.
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