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Parallel Problem Solving from Nature-PPSN VI

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Cover of 'Parallel Problem Solving from Nature-PPSN VI'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Interacting Trajectories in Design Space and Niche Space: A Philosopher Speculates About Evolution
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    Chapter 2 Language as a Complex Adaptive System
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    Chapter 3 Cellular Evolutionary Algorithms: Evaluating the Influence of Ratio
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    Chapter 4 Efficiency and Mutation Strength Adaptation of the ( μ/μ I , λ )-ES in a Noisy Environment
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    Chapter 5 An Analysis of the Configuration Space of the Maximal Constraint Satisfaction Problem
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    Chapter 6 On the Desired Behaviors of Self-Adaptive Evolutionary Algorithms
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    Chapter 7 Practical Implications of New Results in Conservation of Optimizer Performance
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    Chapter 8 Large Deviations, Evolutionary Computation and Comparisons of Algorithms
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    Chapter 9 On the Choice of the Mutation Probability for the (1+1) EA
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    Chapter 10 The Genetic Code-Like Transformations and Their Effect on Learning Functions
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    Chapter 11 Perturbation Theory for Evolutionary Algorithms: Towards an Estimation of Convergence Speed
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    Chapter 12 Statistical Characteristics of Evolution Strategies
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    Chapter 13 Parallel Problem Solving from Nature PPSN VI
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    Chapter 14 Experiments with Tuneable Fitness Landscapes
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    Chapter 15 Introducing a New Persistence Measure
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    Chapter 16 An Analysis of Dynamic Severity and Population Size
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    Chapter 17 Functions as Permutations: Regarding No Free Lunch, Walsh Analysis and Summary Statistics
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    Chapter 18 Distributed Hybrid Genetic Programming for Learning Boolean Functions
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    Chapter 19 Genetic Programming with Dynamic Fitness for a Remote Sensing Application
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    Chapter 20 Genetic Programming Bloat without Semantics
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    Chapter 21 Genetic Programming and Domain Knowledge: Beyond the Limitations of Grammar-Guided Machine Discovery
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    Chapter 22 Polymorphy and Hybridization in Genetically Programmed Networks
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    Chapter 23 Building Optimal Committees of Genetic Programs
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    Chapter 24 Distributed Simulated Annealing for Job Shop Scheduling
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    Chapter 25 Anticipation in Dynamic Optimization: The Scheduling Case
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    Chapter 26 Multirecombinated Evolutionary Algorithms for the Flow Shop Scheduling Problem
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    Chapter 27 GA Based on the UV-Structure Hypothesis and Its Application to JSP
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    Chapter 28 Neighbourhood Based Robustness Applied to Tardiness and Total Flowtime Job Shops
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    Chapter 29 Solving Extended Hybrid-Flow-Shop Problems Using Active Schedule Generation and Genetic Algorithms
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    Chapter 30 A Comparison of Genetic Algorithms for the Static Job Shop Scheduling Problem
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    Chapter 31 An Emperical Study on GAs “Without Parameters”
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    Chapter 32 Using Dynastic Exploring Recombination to Promote Diversity in Genetic Search
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    Chapter 33 Adaptive Control of the Mutation Probability by Fuzzy Logic Controllers
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    Chapter 34 A Comparison of Two Representations for the Fixed Charge Transportation Problem
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    Chapter 35 Invariance, Self-Adaptation and Correlated Mutations in Evolution Strategies
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    Chapter 36 Theoretical Analysis of Simplex Crossover for Real-Coded Genetic Algorithms
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    Chapter 37 Applying Self-Organised Criticality to Evolutionary Algorithms
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    Chapter 38 Genetic Algorithms, Clustering, and the Breaking of Symmetry
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    Chapter 39 Pruefer Numbers and Genetic Algorithms: A Lesson on How the Low Locality of an Encoding Can Harm the Performance of Gas
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    Chapter 40 Median-Selection for Parallel Steady-State Evolution Strategies
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    Chapter 41 The Origination of Diversity by Adaptive Clustering
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    Chapter 42 Symbiotic Combination as an Alternative to Sexual Recombination in Genetic Algorithms
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    Chapter 43 Island Model Cooperating with Speciation for Multimodal Optimization
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    Chapter 44 Optimizing through Co-evolutionary Avalanches
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    Chapter 45 Evolution of Altruism in Viscous Populations: Effects of Altruism on the Evolution of Migrating Behavior
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    Chapter 46 A Game-Theoretic Approach to the Simple Coevolutionary Algorithm
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    Chapter 47 The Number of People with Whom a Man Interacts
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    Chapter 48 NK -landscapes as Test Functions for Evaluation of Host-Parasite Algorithms
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    Chapter 49 Towards Balanced Coevolution
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    Chapter 50 Spatial Games with Adaptive Tit-for-Tats
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    Chapter 51 Competitive Segmentation: A Struggle for Image Space
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    Chapter 52 An Adaptive Algorithm for Constrained Optimization Problems
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    Chapter 53 Test-Case Generator TCG-2 for Nonlinear Parameter Optimisation
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    Chapter 54 Solving CSP Instances Beyond the Phase Transition Using Stochastic Search Algorithms
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    Chapter 55 Steady-State Evolutionary Path Planning, Adaptive Replacement, and Hyper-Diversity
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    Chapter 56 Optimization of Noisy Fitness Functions by Means of Genetic Algorithms Using History of Search
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    Chapter 57 An Efficient Random Number Generation Architecture for Hardware Parallel Genetic Algorithms
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    Chapter 58 An Integrated On-Line Learning System for Evolving Programmable Logic Array Controllers
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    Chapter 59 Selection and Reinforcement Learning for Combinatorial Optimization
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    Chapter 60 Ant Colony Optimization for the Total Weighted Tardiness Problem
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    Chapter 61 Adaptive Fitness Functions for the Satisfiability Problem
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    Chapter 62 Large-Scale Permutation Optimization with the Ordering Messy Genetic Algorithm
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    Chapter 63 A Hybrid GA for the Edge-Biconnectivity Augmentation Problem
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    Chapter 64 A Temporal Representation for GA and TSP
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    Chapter 65 A Comparison of Nature Inspired Heuristics on the Traveling Salesman Problem
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    Chapter 66 A Genetic Algorithm for VLSI Floorplanning
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    Chapter 67 Scalability and Efficiency of Genetic Algorithms for Geometrical Applications
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    Chapter 68 Genetic Optimization of the EPR Spectral Parameters: Algorithm Implementation and Preliminary Results
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    Chapter 69 Fitting Fluorescence Spectra with Genetic Algorithms
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    Chapter 70 Real-Coded Adaptive Range Genetic Algorithm Applied to Transonic Wing Optimization
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    Chapter 71 Stream Cyphers with One- and Two-Dimensional Cellular Automata
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    Chapter 72 Investigating Generalization in the Anticipatory Classifier System
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    Chapter 73 A New Bootstrapping Method to Improve Classification Performance in Learning Classifier Systems
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    Chapter 74 Towards Automatic Domain Knowledge Extraction for Evolutionary Heuristics
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    Chapter 75 Expanding from Discrete to Continuous Estimation of Distribution Algorithms: The ID $$ \mathbb{E} $$ A
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    Chapter 76 A New Genetic Algorithms Working on State Domain Order Statistics
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    Chapter 77 A Factorized Distribution Algorithm Using Single Connected Bayesian Networks
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    Chapter 78 Optimization as Side-Effect of Evolving Allelopathic Diversity
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    Chapter 79 Reaction-Diffusion Model of a Honeybee Colony’s Foraging Behaviour
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    Chapter 80 A Religion-Based Spatial Model for Evolutionary Algorithms
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    Chapter 81 Bayesian Evolutionary Optimization Using Helmholtz Machines
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    Chapter 82 The Pareto Envelope-Based Selection Algorithm for Multiobjective Optimization
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    Chapter 83 A Fast Elitist Non-dominated Sorting Genetic Algorithm for Multi-objective Optimization: NSGA-II
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    Chapter 84 Mechanical Component Design for Multiple Ojectives Using Elitist Non-dominated Sorting GA
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    Chapter 85 On the Assessment of Multiobjective Approaches to the Adaptive Distributed Database Management Problem
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    Chapter 86 A Hierarchical Genetic Algorithm Using Multiple Models for Optimization
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    Chapter 87 Take It EASEA
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    Chapter 88 Evolutionary Computation Visualization: Application to G-PROP
Overall attention for this book and its chapters
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Title
Parallel Problem Solving from Nature-PPSN VI
Published by
Springer Science & Business Media, September 2000
DOI 10.1007/3-540-45356-3
ISBNs
978-3-54-041056-0, 978-3-54-045356-7
Editors

Schoenauer, Marc, Deb, Kalyanmoy, Rudolph, Günther, Yao, Xin, Lutton, Evelyne, Merelo, Juan Julian, Schwefel, Hans-Paul

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The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 34 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 6%
Professor 1 3%
Student > Doctoral Student 1 3%
Student > Ph. D. Student 1 3%
Researcher 1 3%
Other 0 0%
Unknown 28 82%
Readers by discipline Count As %
Environmental Science 2 6%
Engineering 2 6%
Computer Science 1 3%
Biochemistry, Genetics and Molecular Biology 1 3%
Unknown 28 82%