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

  • Conference proceedings
  • © 2013

Overview

Editors:
  1. Oliver Schütze

    1. , Computer Science Department, CINVESTAV-IPN, Mexico City, Mexico

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  2. Carlos A. Coello Coello

    1. , Computer Science Department, CINVESTAV-IPN, Mexico City, Mexico

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  3. Alexandru-Adrian Tantar

    1. , Computer Science and Communications, University of Luxembourg, Luxembourg, Luxembourg

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  4. Emilia Tantar

    1. Computer Science and Communications, Research Unit, University of Luxembourg, Luxembourg, Luxembourg

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  5. Pascal Bouvry

    1. Computer Science, and Communications, University of Luxembourg, Luxembourg, Luxembourg

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  6. Pierre Del Moral

    1. Bordeaux Mathematical Institute, INRIA Bordeaux-Sud Ouest, Université Bordeaux I, Talence Cedex, France

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  7. Pierrick Legrand

    1. Bâtiment Leyteire, UFR Sciences et Modélisation, Université Bordeaux II, Bordeaux, France

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  • Latest research on Probability, Set Oriented Numerics, and Evolutionary Computation
  • Carefully edited book on optimization, operation research, numerical analysis and evolutionary computation
  • Written by leading experts in the field

Part of the book series: Advances in Intelligent Systems and Computing (AISC, volume 175)

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Table of contents (32 papers)

  1. Front Matter

    Pages 1-21
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  2. Cell Mapping and Quasi-stationary Distributions

    1. Front Matter

      Pages 1-1
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  3. Cell Mapping and Quasi-Stationary Distributions

    1. Control of Nonlinear Dynamic Systems with the Cell Mapping Method

      • Jian-Qiao Sun
      Pages 3-18

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

      • Jose Blanchet, Peter Glynn, Shuheng Zheng
      Pages 19-37

  4. Genetic Programming

    1. Front Matter

      Pages 39-39
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    2. Locality in Continuous Fitness-Valued Cases and Genetic Programming Difficulty

      • Edgar Galvan, Leonardo Trujillo, James McDermott, Ahmed Kattan
      Pages 41-56

    3. Analysis and Classification of Epilepsy Stages with Genetic Programming

      • Arturo Sotelo, Enrique Guijarro, Leonardo Trujillo, Luis Coria, Yuliana Martínez
      Pages 57-70

    4. Disparity Map Estimation by Combining Cost Volume Measures Using Genetic Programming

      • Enrique Naredo, Enrique Dunn, Leonardo Trujillo
      Pages 71-86

  5. Evolutionary Multi-objective Optimization

    1. Front Matter

      Pages 87-87
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  6. EvolutionaryMulti-objective Optimization

    1. Finding Evenly Spaced Pareto Fronts for Three-Objective Optimization Problems

      • Heike Trautmann, Günter Rudolph, Christian Dominguez-Medina, Oliver Schütze
      Pages 89-105

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

      • A. Charan Kumari, K. Srinivas, M. P. Gupta
      Pages 107-120

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

      • Gideon Avigad, Erella Eisenstadt, Valery Y. Glizer
      Pages 121-135

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

      • Shaul Salomon, Gideon Avigad, Alex Goldvard, Oliver Schütze
      Pages 137-151

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

      • Adriana Lara, Sergio Alvarado, Shaul Salomon, Gideon Avigad, Carlos A. Coello Coello, Oliver Schütze
      Pages 153-168

  7. Combinatorial Optimization

    1. Front Matter

      Pages 169-169
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    2. A Hyperheuristic Approach for Guiding Enumeration in Constraint Solving

      • Broderick Crawford, Carlos Castro, Eric Monfroy, Ricardo Soto, Wenceslao Palma, Fernando Paredes
      Pages 171-188

    3. Maximum Parsimony Phylogenetic Inference Using Simulated Annealing

      • Jean-Michel Richer, Eduardo Rodriguez-Tello, Karla E. Vazquez-Ortiz
      Pages 189-203

  8. Probabilistic Modeling and Optimization for Emerging Networks

    1. Front Matter

      Pages 205-205
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    2. A Bayesian Network Based Critical Infrastructure Risk Model

      • Thomas Schaberreiter, Pascal Bouvry, Juha Röning, Djamel Khadraoui
      Pages 207-218

  9. Hybrid Probabilistic Models for Real Parameter Optimization and Their Applications

    1. Front Matter

      Pages 219-219
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Keywords

About this book

This book comprises a selection of papers from the EVOLVE 2012 held in Mexico City, Mexico. The aim of the EVOLVE is to build a bridge between probability, set oriented numerics and evolutionary computing, as to identify new common and challenging research aspects.
The conference is also intended to foster a growing interest for robust and efficient methods with a sound theoretical background. EVOLVE is intended to unify theory-inspired methods and cutting-edge techniques ensuring performance guarantee factors. By gathering researchers with different backgrounds, a unified view and vocabulary can emerge where the theoretical advancements
may echo in different domains. Summarizing, the EVOLVE focuses on challenging aspects arising at the passage from theory to new paradigms and aims to provide a unified view while raising questions related to reliability,  performance guarantees and modeling. The papers of the EVOLVE 2012 make a contribution to this goal.

Editors and Affiliations

  • , Computer Science Department, CINVESTAV-IPN, Mexico City, Mexico

    Oliver Schütze, Carlos A. Coello Coello

  • , Computer Science and Communications, University of Luxembourg, Luxembourg, Luxembourg

    Alexandru-Adrian Tantar

  • Computer Science and Communications, Research Unit, University of Luxembourg, Luxembourg, Luxembourg

    Emilia Tantar

  • Computer Science, and Communications, University of Luxembourg, Luxembourg, Luxembourg

    Pascal Bouvry

  • Bordeaux Mathematical Institute, INRIA Bordeaux-Sud Ouest, Université Bordeaux I, Talence Cedex, France

    Pierre Del Moral

  • Bâtiment Leyteire, UFR Sciences et Modélisation, Université Bordeaux II, Bordeaux, France

    Pierrick Legrand

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