EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation II

ISBN: 978-3-642-31518-3 (Print) 978-3-642-31519-0 (Online)

Table of contents (32 chapters)

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  1. Front Matter

    Pages 1-21

  2. Cell Mapping and Quasi-Stationary Distributions

    1. Front Matter

      Pages 1-1

    2. No Access

      Book Chapter

      Pages 3-18

      Control of Nonlinear Dynamic Systems with the Cell Mapping Method

    3. No Access

      Book Chapter

      Pages 19-37

      Empirical Analysis of a Stochastic Approximation Approach for Computing Quasi-stationary Distributions

  3. Genetic Programming

    1. Front Matter

      Pages 39-39

    2. No Access

      Book Chapter

      Pages 41-56

      Locality in Continuous Fitness-Valued Cases and Genetic Programming Difficulty

    3. No Access

      Book Chapter

      Pages 57-70

      Analysis and Classification of Epilepsy Stages with Genetic Programming

    4. No Access

      Book Chapter

      Pages 71-86

      Disparity Map Estimation by Combining Cost Volume Measures Using Genetic Programming

  4. EvolutionaryMulti-objective Optimization

    1. Front Matter

      Pages 87-87

    2. No Access

      Book Chapter

      Pages 89-105

      Finding Evenly Spaced Pareto Fronts for Three-Objective Optimization Problems

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      Book Chapter

      Pages 107-120

      Software Requirements Optimization Using Multi-Objective Quantum-Inspired Hybrid Differential Evolution

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      Book Chapter

      Pages 121-135

      Evolving a Pareto Front for an Optimal Bi-objective Robust Interception Problem with Imperfect Information

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      Book Chapter

      Pages 137-151

      PSA – A New Scalable Space Partition Based Selection Algorithm for MOEAs

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      Book Chapter

      Pages 153-168

      The Gradient Free Directed Search Method as Local Search within Multi-Objective Evolutionary Algorithms

  5. Combinatorial Optimization

    1. Front Matter

      Pages 169-169

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      Book Chapter

      Pages 171-188

      A Hyperheuristic Approach for Guiding Enumeration in Constraint Solving

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      Book Chapter

      Pages 189-203

      Maximum Parsimony Phylogenetic Inference Using Simulated Annealing

  6. Probabilistic Modeling and Optimization for Emerging Networks

    1. Front Matter

      Pages 205-205

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      Book Chapter

      Pages 207-218

      A Bayesian Network Based Critical Infrastructure Risk Model

  7. Hybrid Probabilistic Models for Real Parameter Optimization and their Applications

    1. Front Matter

      Pages 219-219

    2. No Access

      Book Chapter

      Pages 221-235

      Adequate Variance Maintenance in a Normal EDA via the Potential-Selection Method

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      Book Chapter

      Pages 237-249

      Linkage Learning Using Graphical Markov Model Structure: An Experimental Study

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      Book Chapter

      Pages 251-265

      A Comparison Study of PSO Neighborhoods

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      Book Chapter

      Pages 267-282

      hypDE: A Hyper-Heuristic Based on Differential Evolution for Solving Constrained Optimization Problems

  8. Evolutionary Computation for Vision, Graphics, and Robotics

    1. Front Matter

      Pages 283-283

    2. No Access

      Book Chapter

      Pages 285-297

      Evolutionary Computation Applied to the Automatic Design of Artificial Neural Networks and Associative Memories

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      Book Chapter

      Pages 299-311

      Segmentation of Blood Cell Images Using Evolutionary Methods

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      Book Chapter

      Pages 313-325

      Fast Circle Detection Using Harmony Search Optimization

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