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Genetic and Evolutionary Computation — GECCO 2004

Genetic and Evolutionary Computation Conference, Seattle, WA, USA, June 26–30, 2004 Proceedings, Part II

  • Conference proceedings
  • © 2004
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Overview

Editors:
  1. Kalyanmoy Deb

    1. Indian Institute of Technology Kanpur, Department of Mechanical Engineering, Kanpur Genetic Algorithms Laboratory (KanGAL), 208016, India

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 3103)

Included in the following conference series:

Conference proceedings info: GECCO 2004.

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Table of contents (165 papers)

  1. Front Matter

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  2. Genetic Algorithms (Continued)

    1. PID Controller Tuning for Stable and Unstable Processes Applying GA

      • Marco Antonio Paz-Ramos, Jose Torres-Jimenez, Enrique Quintero-Marmol-Marquez, Hugo Estrada-Esquivel
      Pages 1-10
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    2. Dynamic Uniform Scaling for Multiobjective Genetic Algorithms

      • Gerulf K. M. Pedersen, David E. Goldberg
      Pages 11-23
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    3. Parameter-Less Hierarchical BOA

      • Martin Pelikan, Tz-Kai Lin
      Pages 24-35
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    4. Computational Complexity and Simulation of Rare Events of Ising Spin Glasses

      • Martin Pelikan, Jiri Ocenasek, Simon Trebst, Matthias Troyer, Fabien Alet
      Pages 36-47
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    5. Fitness Inheritance in the Bayesian Optimization Algorithm

      • Martin Pelikan, Kumara Sastry
      Pages 48-59
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    6. Limit Cycle Prediction in Multivariable Nonlinear Systems Using Genetic Algorithms

      • Farzan Rashidi, Mehran Rashidi
      Pages 60-68
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    7. Evolving Reusable Neural Modules

      • Joseph Reisinger, Kenneth O. Stanley, Risto Miikkulainen
      Pages 69-81
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    8. How Are We Doing? Predicting Evolutionary Algorithm Performance

      • Mark A. Renslow, Brenda Hinkemeyer, Bryant A. Julstrom
      Pages 82-89
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    9. Introduction of a New Selection Parameter in Genetic Algorithm for Constrained Reliability Design Problems

      • Laure Rigal, Bruno Castanier, Philippe Castagliola
      Pages 90-101
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    10. Improving the Performance of a Genetic Algorithm Using a Variable-Reordering Algorithm

      • Eduardo Rodriguez-Tello, Jose Torres-Jimenez
      Pages 102-113
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    11. Designing Competent Mutation Operators Via Probabilistic Model Building of Neighborhoods

      • Kumara Sastry, David E. Goldberg
      Pages 114-125
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    12. Let’s Get Ready to Rumble: Crossover Versus Mutation Head to Head

      • Kumara Sastry, David E. Goldberg
      Pages 126-137
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    13. Classification with Scaled Genetic Algorithms in a Coevolutionary Setting

      • Lothar M. Schmitt
      Pages 138-149
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    14. New Epistasis Measures for Detecting Independently Optimizable Partitions of Variables

      • Dong-Il Seo, Sung-Soon Choi, Byung-Ro Moon
      Pages 150-161
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    15. Clustering with Niching Genetic K-means Algorithm

      • Weiguo Sheng, Allan Tucker, Xiaohui Liu
      Pages 162-173
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    16. A Comparison of Genetic Programming and Genetic Algorithms in the Design of a Robust, Saturated Control System

      • Andrea Soltoggio
      Pages 174-185
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    17. Upper Bounds on the Time and Space Complexity of Optimizing Additively Separable Functions

      • Matthew J. Streeter
      Pages 186-197
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    18. Winnowing Wheat from Chaff: The Chunking GA

      • Hal Stringer, Annie S. Wu
      Pages 198-209
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    19. An Effective Chromosome Representation for Evolving Flexible Job Shop Schedules

      • Joc Cing Tay, Djoko Wibowo
      Pages 210-221
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Other volumes

  1. Genetic and Evolutionary Computation – GECCO 2004

  2. Genetic and Evolutionary Computation – GECCO 2004

Keywords

About this book

The two volume set LNCS 3102/3103 constitutes the refereed proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2004, held in Seattle, WA, USA, in June 2004.

The 230 revised full papers and 104 poster papers presented were carefully reviewed and selected from 460 submissions. The papers are organized in topical sections on artificial life, adaptive behavior, agents, and ant colony optimization; artificial immune systems, biological applications; coevolution; evolutionary robotics; evolution strategies and evolutionary programming; evolvable hardware; genetic algorithms; genetic programming; learning classifier systems; real world applications; and search-based software engineering.


Editors and Affiliations

  • Indian Institute of Technology Kanpur, Department of Mechanical Engineering, Kanpur Genetic Algorithms Laboratory (KanGAL), 208016, India

    Kalyanmoy Deb

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