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Parallel Problem Solving from Nature – PPSN XIII : 13th International Conference, Ljubljana, Slovenia, September 13-17, 2014. Proceedings

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Cover of 'Parallel Problem Solving from Nature – PPSN XIII : 13th International Conference, Ljubljana, Slovenia, September 13-17, 2014. Proceedings'

Table of Contents

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    Book Overview
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    Chapter 1 Some Computational Aspects of Robot Kinematic Redundancy
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    Chapter 2 Power Distribution Network Reconfiguration by Evolutionary Integer Programming
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    Chapter 3 In Vivo Veritas: Towards the Evolution of Things
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    Chapter 4 Online Black-Box Algorithm Portfolios for Continuous Optimization
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    Chapter 5 Shuffle and Mate: A Dynamic Model for Spatially Structured Evolutionary Algorithms
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    Chapter 6 How to Assess Step-Size Adaptation Mechanisms in Randomised Search
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    Chapter 7 Maximum Likelihood-Based Online Adaptation of Hyper-Parameters in CMA-ES
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    Chapter 8 Run-Time Parameter Selection and Tuning for Energy Optimization Algorithms
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    Chapter 9 Towards a Method for Automatic Algorithm Configuration: A Design Evaluation Using Tuners
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    Chapter 10 Parameter Prediction Based on Features of Evolved Instances for Ant Colony Optimization and the Traveling Salesperson Problem
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    Chapter 11 Self-Adaptive Genotype-Phenotype Maps: Neural Networks as a Meta-Representation
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    Chapter 12 The Baldwin Effect Hinders Self-Adaptation
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    Chapter 13 On Low Complexity Acceleration Techniques for Randomized Optimization
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    Chapter 14 Stopping Criteria for Multimodal Optimization
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    Chapter 15 VLR: A Memory-Based Optimization Heuristic
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    Chapter 16 A Differential Evolution Algorithm for the Permutation Flowshop Scheduling Problem with Total Flow Time Criterion
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    Chapter 17 A Taxonomy of Heterogeneity and Dynamics in Particle Swarm Optimisation
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    Chapter 18 Derivation of a Micro-Macro Link for Collective Decision-Making Systems
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    Chapter 19 Messy Coding in the XCS Classifier System for Sequence Labeling
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    Chapter 20 Reevaluating Exponential Crossover in Differential Evolution
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    Chapter 21 An Extended Michigan-Style Learning Classifier System for Flexible Supervised Learning, Classification, and Data Mining
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    Chapter 22 A Cooperative Evolutionary Approach to Learn Communities in Multilayer Networks
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    Chapter 23 Novelty Search in Competitive Coevolution
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    Chapter 24 An Immune-Inspired Algorithm for the Set Cover Problem
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    Chapter 25 Natural Gradient Approach for Linearly Constrained Continuous Optimization
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    Chapter 26 Evolutionary Constrained Optimization for a Jupiter Capture
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    Chapter 27 Viability Principles for Constrained Optimization Using a (1+1)-CMA-ES
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    Chapter 28 On the Life-Long Learning Capabilities of a NELLI*: A Hyper-Heuristic Optimisation System
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    Chapter 29 Adaptation in Nonlinear Learning Models for Nonstationary Tasks
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    Chapter 30 Parallel Problem Solving from Nature – PPSN XIII
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    Chapter 31 Evolving Mixtures of n-gram Models for Sequencing and Schedule Optimization
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    Chapter 32 A Study on Multimemetic Estimation of Distribution Algorithms
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    Chapter 33 Factoradic Representation for Permutation Optimisation
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    Chapter 34 Combining Model-Based EAs for Mixed-Integer Problems
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    Chapter 35 A New EDA by a Gradient-Driven Density
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    Chapter 36 From Expected Improvement to Investment Portfolio Improvement: Spreading the Risk in Kriging-Based Optimization
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    Chapter 37 Distance Measures for Permutations in Combinatorial Efficient Global Optimization
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    Chapter 38 Parallel Problem Solving from Nature – PPSN XIII
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    Chapter 39 Compressing Regular Expression Sets for Deep Packet Inspection
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    Chapter 40 Inferring and Exploiting Problem Structure with Schema Grammar
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    Chapter 41 Bent Function Synthesis by Means of Cartesian Genetic Programming
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    Chapter 42 Population Exploration on Genotype Networks in Genetic Programming
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    Chapter 43 Improving Genetic Programming with Behavioral Consistency Measure
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    Chapter 44 On Effective and Inexpensive Local Search Techniques in Genetic Programming Regression
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    Chapter 45 Combining Semantically-Effective and Geometric Crossover Operators for Genetic Programming
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    Chapter 46 On the Locality of Standard Search Operators in Grammatical Evolution
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    Chapter 47 Recurrent Cartesian Genetic Programming
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    Chapter 48 An Analysis on Selection for High-Resolution Approximations in Many-Objective Optimization
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    Chapter 49 A Multiobjective Evolutionary Optimization Framework for Protein Purification Process Design
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    Chapter 50 Automatic Design of Evolutionary Algorithms for Multi-Objective Combinatorial Optimization
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    Chapter 51 Generic Postprocessing via Subset Selection for Hypervolume and Epsilon-Indicator
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    Chapter 52 A Provably Asymptotically Fast Version of the Generalized Jensen Algorithm for Non-dominated Sorting
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    Chapter 53 Clustering-Based Selection for Evolutionary Many-Objective Optimization
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    Chapter 54 On the Impact of Multiobjective Scalarizing Functions
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    Chapter 55 Multi-objective Quadratic Assignment Problem Instances Generator with a Known Optimum Solution
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    Chapter 56 Optimized Approximation Sets for Low-Dimensional Benchmark Pareto Fronts
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    Chapter 57 Start Small, Grow Big? Saving Multi-objective Function Evaluations
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    Chapter 58 Queued Pareto Local Search for Multi-Objective Optimization
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    Chapter 59 Distance-Based Analysis of Crossover Operators for Many-Objective Knapsack Problems
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    Chapter 60 Discovery of Implicit Objectives by Compression of Interaction Matrix in Test-Based Problems
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    Chapter 61 Local Optimal Sets and Bounded Archiving on Multi-objective NK-Landscapes with Correlated Objectives
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    Chapter 62 Racing Multi-objective Selection Probabilities
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    Chapter 63 Shake Them All!
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    Chapter 64 MH-MOEA: A New Multi-Objective Evolutionary Algorithm Based on the Maximin Fitness Function and the Hypervolume Indicator
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    Chapter 65 Empirical Performance of the Approximation of the Least Hypervolume Contributor
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    Chapter 66 A Portfolio Optimization Approach to Selection in Multiobjective Evolutionary Algorithms
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    Chapter 67 Using a Family of Curves to Approximate the Pareto Front of a Multi-Objective Optimization Problem
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    Chapter 68 Travelling Salesman Problem Solved ‘in materio’ by Evolved Carbon Nanotube Device
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    Chapter 69 Randomized Parameter Settings for Heterogeneous Workers in a Pool-Based Evolutionary Algorithm
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    Chapter 70 PaDe: A Parallel Algorithm Based on the MOEA/D Framework and the Island Model
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    Chapter 71 Evolution-In-Materio: Solving Machine Learning Classification Problems Using Materials
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    Chapter 72 An Analysis of Migration Strategies in Island-Based Multimemetic Algorithms
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    Chapter 73 Tuning Evolutionary Multiobjective Optimization for Closed-Loop Estimation of Chromatographic Operating Conditions
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    Chapter 74 A Geometrical Approach to the Incompatible Substructure Problem in Parallel Self-Assembly
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    Chapter 75 Application of Evolutionary Methods to Semiconductor Double-Chirped Mirrors Design
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    Chapter 76 Evolving Neural Network Weights for Time-Series Prediction of General Aviation Flight Data
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    Chapter 77 Random Partial Neighborhood Search for University Course Timetabling Problem
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    Chapter 78 Balancing Bicycle Sharing Systems: An Analysis of Path Relinking and Recombination within a GRASP Hybrid
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    Chapter 79 Multiobjective Selection of Input Sensors for SVR Applied to Road Traffic Prediction
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    Chapter 80 Evolving DPA-Resistant Boolean Functions
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    Chapter 81 Combining Evolutionary Computation and Algebraic Constructions to Find Cryptography-Relevant Boolean Functions
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    Chapter 82 A Memetic Algorithm for Multi Layer Hierarchical Ring Network Design
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    Chapter 83 Scheduling the English Football League with a Multi-objective Evolutionary Algorithm
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    Chapter 84 Coupling Evolution and Information Theory for Autonomous Robotic Exploration
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    Chapter 85 Local Optima and Weight Distribution in the Number Partitioning Problem
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    Chapter 86 Quasi-Stability of Real Coded Finite Populations
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    Chapter 87 On the Use of Evolution Strategies for Optimization on Spherical Manifolds
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    Chapter 88 Unbiased Black-Box Complexity of Parallel Search
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    Chapter 89 A Generalized Markov-Chain Modelling Approach to (1,λ)-ES Linear Optimization
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    Chapter 90 Level-Based Analysis of Genetic Algorithms and Other Search Processes
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    Chapter 91 Maximizing Submodular Functions under Matroid Constraints by Multi-objective Evolutionary Algorithms
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    Chapter 92 On the Runtime Analysis of Fitness Sharing Mechanisms
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    Chapter 93 Runtime Analysis of Evolutionary Algorithms on Randomly Constructed High-Density Satisfiable 3-CNF Formulas
Overall attention for this book and its chapters
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Title
Parallel Problem Solving from Nature – PPSN XIII : 13th International Conference, Ljubljana, Slovenia, September 13-17, 2014. Proceedings
Published by
Springer, Cham, January 2014
DOI 10.1007/978-3-319-10762-2
ISBNs
978-3-31-910761-5, 978-3-31-910762-2
Editors

Thomas Bartz-Beielstein, Jürgen Branke, Bogdan Filipič, Jim Smith

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Mendeley readers

The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
South Africa 1 9%
Unknown 10 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 18%
Student > Ph. D. Student 2 18%
Professor 1 9%
Professor > Associate Professor 1 9%
Student > Postgraduate 1 9%
Other 0 0%
Unknown 4 36%
Readers by discipline Count As %
Economics, Econometrics and Finance 2 18%
Psychology 2 18%
Computer Science 1 9%
Environmental Science 1 9%
Mathematics 1 9%
Other 1 9%
Unknown 3 27%