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Parallel Evolutionary Computations

  • Nadia Nedjah
  • Luiza de Macedo Mourelle
  • Enrique Alba

Part of the Studies in Computational Intelligence book series (SCI, volume 22)

Table of contents

  1. Front Matter
    Pages I-XXIII
  2. Parallel Evolutionary Optimization

    1. Front Matter
      Pages I-XXIII
    2. Hernán Aguirre, Kiyoshi Tanaka
      Pages 3-31
    3. Francisco Luna, Antonio J. Nebro, Enrique Alba
      Pages 33-56
  3. Parallel Hardware for Genetic Algorithms

    1. Front Matter
      Pages I-XXIII
    2. Nadia Nedjah, Luiza de Macedo Mourelle
      Pages 59-69
    3. Miguel A. Vega Rodríguez, Juan A. Gómez Pulido, Juan M. Sánchez Pérez, José M. Granado Criado, Manuel Rubio del Solar
      Pages 71-93
  4. Distributed Evolutionary Computation

    1. Front Matter
      Pages I-XXIII
    2. Enrique Alba, Gabriel Luque
      Pages 97-115
    3. N. Melab, E-G. Talbi, S. Cahon
      Pages 117-132
  5. Parallel Particle Swarm Optimization

    1. Front Matter
      Pages I-XXIII
    2. Shu-Chuan Chu, Jeng-Shyang Pan
      Pages 159-175
  6. Back Matter
    Pages 199-201

About this book

Introduction

"Parallel Evolutionary Computation" focuses on the aspects related to the parallelization of evolutionary computations, such as parallel genetic operators, parallel fitness evaluation, distributed genetic algorithms, and parallel hardware implementations, as well as on their impact on several applications.
The book is divided into four parts. The first part deals with a clear software-like and algorithmic vision on parallel evolutionary optimizations. The second part is about hardware implementations of genetic algorithms, a valuable topic which is hard to find in the present literature. The third part treats the problem of distributed evolutionary computation and presents three interesting applications wherein parallel EC new ideas are featured. Finally, the last part deals with the up-to-date field of parallel particle swarm optimization to illustrate the intrinsic similarities and potential extensions to techniques in this domain. The book offers a wide spectrum of sample works developed in leading research throughout the world about parallel implementations of efficient techniques at the heart of computational intelligence. It will be useful both for beginners and experienced researchers in the field of computational intelligence.


Keywords

Hardware algorithm algorithms computational intelligence evolution evolutionary algorithm evolutionary computation genetic algorithms genetic operator intelligence multi-objective optimization operator optimization particle swarm particle swarm optimization

Editors and affiliations

  • Nadia Nedjah
    • 1
  • Luiza de Macedo Mourelle
    • 2
  • Enrique Alba
    • 3
  1. 1.Department of System Engineering and ComputationFaculty of Engineering State University of Rio de Janeiro Rua São Francisco XavierRio de JaneiroBrazil
  2. 2.Department of System Engineering and ComputationFaculty of Engineering State University of Rio de Janeiro Rua São Francisco XavierRio de JaneiroBrazil
  3. 3.Depto. of Lenguajes y Ciencias de la Computación Campus de TeatinosUniversidad de MálagaMálagaSpain

Bibliographic information

  • DOI https://doi.org/10.1007/3-540-32839-4
  • Copyright Information Springer 2006
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-540-32837-7
  • Online ISBN 978-3-540-32839-1
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • Buy this book on publisher's site