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Parameter Setting in Evolutionary Algorithms

Overview of attention for book
Parameter Setting in Evolutionary Algorithms
Springer-Verlag Berlin Heidelberg

Table of Contents

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    Book Overview
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    Chapter 1 Parameter Setting in EAs: a 30 Year Perspective
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    Chapter 2 Parameter Setting in Evolutionary Algorithms
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    Chapter 3 Self-Adaptation in Evolutionary Algorithms
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    Chapter 4 Adaptive Strategies for Operator Allocation
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    Chapter 5 Sequential Parameter Optimization Applied to Self-Adaptation for Binary-Coded Evolutionary Algorithms
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    Chapter 6 Combining Meta-EAs and Racing for Difficult EA Parameter Tuning Tasks
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    Chapter 7 Genetic Programming: Parametric Analysis of Structure Altering Mutation Techniques
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    Chapter 8 Parameter Sweeps for Exploring Parameter Spaces of Genetic and Evolutionary Algorithms
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    Chapter 9 Adaptive Population Sizing Schemes in Genetic Algorithms
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    Chapter 10 Population Sizing to Go: Online Adaptation Using Noise and Substructural Measurements
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    Chapter 11 Parameter-less Hierarchical Bayesian Optimization Algorithm
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    Chapter 12 Evolutionary Multi-Objective Optimization Without Additional Parameters
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    Chapter 13 Parameter Setting in Parallel Genetic Algorithms
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    Chapter 14 Parameter Setting in Evolutionary Algorithms
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    Chapter 15 Parameter Setting in Evolutionary Algorithms
Overall attention for this book and its chapters
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#12 of 402)
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

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