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Parallel Architectures and Bioinspired Algorithms

  • Book
  • © 2012

Overview

Editors:
  1. Francisco Fernández de Vega

    1. Centro Universitario de Mérida, Universidad de Extremadura, Mérida, Spain

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  2. José Ignacio Hidalgo Pérez

    1. Facultad de Informática, Universidad Complutense de Madrid, Madrid, Spain

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  3. Juan Lanchares

    1. Facultad de Informática, Universidad Complutense de Madrid, Madrid, Spain

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  • Recent research in Parallel Architectures and Bioinspired Algorithms
  • Presents an important applicaton of bioinspired algorithms
  • Written by leading experts in the field

Part of the book series: Studies in Computational Intelligence (SCI, volume 415)

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Table of contents (12 chapters)

  1. Front Matter

    Pages 1-5
    Download chapter PDF

  2. Introduction

    • Francisco Fernández de Vega, J. Ignacio Hidalgo, Juan Lanchares
    Pages 1-6

  3. Creating and Debugging Performance CUDA C

    • W. B. Langdon
    Pages 7-50

  4. Optimizing Shape Design with Distributed Parallel Genetic Programming on GPUs

    • Simon Harding, W. Banzhaf
    Pages 51-75

  5. Characterizing Fault-Tolerance in Evolutionary Algorithms

    • Daniel Lombraña González, Juan Luis Jiménez Laredo, Francisco Fernández de Vega, Juan Julián Merelo Guervós
    Pages 77-99

  6. Comparison of Frameworks for Parallel Multiobjective Evolutionary Optimization in Dynamic Problems

    • Mario Cámara, Julio Ortega, Francisco de Toro
    Pages 101-123

  7. An Empirical Study of Parallel and Distributed Particle Swarm Optimization

    • Leonardo Vanneschi, Daniele Codecasa, Giancarlo Mauri
    Pages 125-150

  8. The Generalized Island Model

    • Dario Izzo, Marek Ruciński, Francesco Biscani
    Pages 151-169

  9. Evolutionary Associative Memories through Genetic Programming

    • Juan Villegas-Cortez, Gustavo Olague, Humberto Sossa, Carlos Avilés
    Pages 171-188

  10. Parallel Architectures for Improving the Performance of a GA Based Trading System

    • Iván Contreras, J. Ignacio Hidalgo, Laura Nuñez-Letamendía, Yiyi Jiang
    Pages 189-218

  11. A Knowledge-Based Operator for a Genetic Algorithm which Optimizes the Distribution of Sparse Matrix Data

    • Una-May O’Reilly, Nadya Bliss, Sanjeev Mohindra, Julie Mullen, Eric Robinson
    Pages 219-241

  12. Evolutive Approaches for Variable Selection Using a Non-parametric Noise Estimator

    • Alberto Guillén, Dušan Sovilj, Mark van Heeswijk, Luis Javier Herrera, Amaury Lendasse, Héctor Pomares et al.
    Pages 243-266

  13. A Chemical Evolutionary Mechanism for Instantiating Service-Based Applications

    • Maurizio Giordano, Claudia Di Napoli
    Pages 267-286

  14. Back Matter

    Pages 0--1
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Keywords

About this book

This monograph presents examples of best practices when combining bioinspired algorithms with parallel architectures. The book includes recent work by leading researchers in the field and offers a map with the main paths already explored and new ways towards the future.

Parallel Architectures and Bioinspired Algorithms will be of value to both specialists in Bioinspired Algorithms, Parallel and Distributed Computing, as well as computer science students trying to understand the present and the future of Parallel Architectures and Bioinspired Algorithms.

Editors and Affiliations

  • Centro Universitario de Mérida, Universidad de Extremadura, Mérida, Spain

    Francisco Fernández de Vega

  • Facultad de Informática, Universidad Complutense de Madrid, Madrid, Spain

    José Ignacio Hidalgo Pérez, Juan Lanchares

Bibliographic Information

  • Book Title: Parallel Architectures and Bioinspired Algorithms

  • Editors: Francisco Fernández de Vega, José Ignacio Hidalgo Pérez, Juan Lanchares

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-642-28789-3

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer-Verlag Berlin Heidelberg 2012

  • Hardcover ISBN: 978-3-642-28788-6Published: 28 April 2012

  • Softcover ISBN: 978-3-642-42736-7Published: 09 May 2014

  • eBook ISBN: 978-3-642-28789-3Published: 27 April 2012

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: VI, 290

  • Topics: Computational Intelligence, Artificial Intelligence

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