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Parallel Problem Solving from Nature, PPSN XI

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Cover of 'Parallel Problem Solving from Nature, PPSN XI'

Table of Contents

  1. Altmetric Badge
    Book Overview
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    Chapter 1 Optimal Fixed and Adaptive Mutation Rates for the LeadingOnes Problem
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    Chapter 2 Mirrored Sampling and Sequential Selection for Evolution Strategies
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    Chapter 3 Optimisation and Generalisation: Footprints in Instance Space
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    Chapter 4 Adaptive Drift Analysis
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    Chapter 5 Optimizing Monotone Functions Can Be Difficult
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    Chapter 6 Log-Linear Convergence of the Scale-Invariant (μ/μ w ,λ)-ES and Optimal μ for Intermediate Recombination for Large Population Sizes
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    Chapter 7 Exploiting Overlap When Searching for Robust Optima
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    Chapter 8 Benchmarking Evolutionary Algorithms: Towards Exploratory Landscape Analysis
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    Chapter 9 Parallel Problem Solving from Nature, PPSN XI
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    Chapter 10 When Does Dependency Modelling Help? Using a Randomized Landscape Generator to Compare Algorithms in Terms of Problem Structure
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    Chapter 11 Parallel Problem Solving from Nature, PPSN XI
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    Chapter 12 Differential Mutation Based on Population Covariance Matrix
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    Chapter 13 General Lower Bounds for the Running Time of Evolutionary Algorithms
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    Chapter 14 A Binary Encoding Supporting Both Mutation and Recombination
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    Chapter 15 Towards Analyzing Recombination Operators in Evolutionary Search
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    Chapter 16 Bidirectional Relation between CMA Evolution Strategies and Natural Evolution Strategies
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    Chapter 17 A Fine-Grained View of GP Locality with Binary Decision Diagrams as Ant Phenotypes
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    Chapter 18 Drift Analysis with Tail Bounds
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    Chapter 19 More Effective Crossover Operators for the All-Pairs Shortest Path Problem
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    Chapter 20 Comparison-Based Adaptive Strategy Selection with Bandits in Differential Evolution
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    Chapter 21 Fixed Parameter Evolutionary Algorithms and Maximum Leaf Spanning Trees: A Matter of Mutation
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    Chapter 22 An Archive Maintenance Scheme for Finding Robust Solutions
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    Chapter 23 Experimental Supplements to the Theoretical Analysis of Migration in the Island Model
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    Chapter 24 General Scheme for Analyzing Running Times of Parallel Evolutionary Algorithms
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    Chapter 25 Negative Drift in Populations
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    Chapter 26 Log(λ) Modifications for Optimal Parallelism
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    Chapter 27 The Linkage Tree Genetic Algorithm
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    Chapter 28 An Analysis of the XOR Dynamic Problem Generator Based on the Dynamical System
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    Chapter 29 The Role of Degenerate Robustness in the Evolvability of Multi-agent Systems in Dynamic Environments
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    Chapter 30 Evolutionary Learning of Technical Trading Rules without Data-Mining Bias
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    Chapter 31 Using Computational Intelligence to Identify Performance Bottlenecks in a Computer System
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    Chapter 32 Selecting Small Audio Feature Sets in Music Classification by Means of Asymmetric Mutation
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    Chapter 33 Globally Induced Model Trees: An Evolutionary Approach
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    Chapter 34 Open-Ended Evolutionary Robotics: An Information Theoretic Approach
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    Chapter 35 A Novel Similarity-Based Crossover for Artificial Neural Network Evolution
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    Chapter 36 Indirect Encoding of Neural Networks for Scalable Go
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    Chapter 37 Comparison-Based Optimizers Need Comparison-Based Surrogates
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    Chapter 38 A Cooperative Coevolutionary Approach to Partitional Clustering
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    Chapter 39 Feature Selection for Multi-purpose Predictive Models: A Many-Objective Task
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    Chapter 40 Incorporating Domain Knowledge into Evolutionary Computing for Discovering Gene-Gene Interaction.
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    Chapter 41 The Application of Pittsburgh-Style Learning Classifier Systems to Address Genetic Heterogeneity and Epistasis in Association Studies
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    Chapter 42 Threshold Selection, Mitosis and Dual Mutation in Cooperative Co-evolution: Application to Medical 3D Tomography
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    Chapter 43 Comparative Analysis of Search and Score Metaheuristics for Bayesian Network Structure Learning Using Node Juxtaposition Distributions
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    Chapter 44 Analyzing the Credit Default Swap Market Using Cartesian Genetic Programming
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    Chapter 45 A Memetic Cooperative Optimization Schema and Its Application to the Tool Switching Problem
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    Chapter 46 Ownership and Trade in Spatial Evolutionary Memetic Games
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    Chapter 47 A Hyper-Heuristic Approach to Strip Packing Problems
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    Chapter 48 Asymptotic Analysis of Computational Multi-Agent Systems
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    Chapter 49 Path-Guided Mutation for Stochastic Pareto Local Search Algorithms
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    Chapter 50 Scheduling English Football Fixtures over the Holiday Period Using Hyper-heuristics
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    Chapter 51 Graph Clustering Based Model Building
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    Chapter 52 How to Choose Solutions for Local Search in Multiobjective Combinatorial Memetic Algorithms
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    Chapter 53 Secure and Task Abortion Aware GA-Based Hybrid Metaheuristics for Grid Scheduling
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    Chapter 54 A Memetic Algorithm for the Pickup and Delivery Problem with Time Windows Using Selective Route Exchange Crossover
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    Chapter 55 Ant Based Hyper Heuristics with Space Reduction: A Case Study of the p-Median Problem
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    Chapter 56 A Study of Multi-parent Crossover Operators in a Memetic Algorithm
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    Chapter 57 A Hybrid Genetic Algorithm for the Traveling Salesman Problem Using Generalized Partition Crossover
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    Chapter 58 A Memetic Algorithm with Non Gradient-Based Local Search Assisted by a Meta-model
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    Chapter 59 Theoretically Investigating Optimal μ-Distributions for the Hypervolume Indicator: First Results for Three Objectives
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    Chapter 60 Convergence Rates of (1+1) Evolutionary Multiobjective Optimization Algorithms
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    Chapter 61 Tight Bounds for the Approximation Ratio of the Hypervolume Indicator
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    Chapter 62 Evolutionary Multiobjective Optimization Algorithm as a Markov System
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    Chapter 63 A Natural Evolution Strategy for Multi-objective Optimization
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    Chapter 64 Solving Multiobjective Optimization Problem by Constraint Optimization
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    Chapter 65 Enhancing Diversity for Average Ranking Method in Evolutionary Many-Objective Optimization
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    Chapter 66 Objective Space Partitioning Using Conflict Information for Many-Objective Optimization
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    Chapter 67 How Crossover Speeds Up Evolutionary Algorithms for the Multi-criteria All-Pairs-Shortest-Path Problem
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    Chapter 68 Path Relinking on Many-Objective NK-Landscapes
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    Chapter 69 In Search of Equitable Solutions Using Multi-objective Evolutionary Algorithms
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    Chapter 70 Stopping Criteria for Genetic Algorithms with Application to Multiobjective Optimization
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    Chapter 71 Defining and Optimizing Indicator-Based Diversity Measures in Multiobjective Search
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    Chapter 72 On Expected-Improvement Criteria for Model-based Multi-objective Optimization
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    Chapter 73 Parameter Tuning Boosts Performance of Variation Operators in Multiobjective Optimization
Attention for Chapter 49: Path-Guided Mutation for Stochastic Pareto Local Search Algorithms
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Chapter title
Path-Guided Mutation for Stochastic Pareto Local Search Algorithms
Chapter number 49
Book title
Parallel Problem Solving from Nature, PPSN XI
Published by
Springer Berlin Heidelberg, January 2010
DOI 10.1007/978-3-642-15844-5_49
Book ISBNs
978-3-64-215843-8, 978-3-64-215844-5
Authors

Madalina M. Drugan, Dirk Thierens

Editors

Robert Schaefer, Carlos Cotta, Joanna Kołodziej, Günter Rudolph

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 6%
Unknown 15 94%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 3 19%
Researcher 3 19%
Professor 2 13%
Student > Ph. D. Student 2 13%
Professor > Associate Professor 2 13%
Other 2 13%
Unknown 2 13%
Readers by discipline Count As %
Computer Science 9 56%
Mathematics 2 13%
Chemical Engineering 2 13%
Unknown 3 19%

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