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Advances of Evolutionary Computation: Methods and Operators

  • Book
  • © 2016

Overview

Authors:
  1. Erik Cuevas

    1. Departamento de Electrónica, CUCEI, Universidad de Guadalajara, Guadalajara, Mexico

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  2. Margarita Arimatea Díaz Cortés

    1. Institut für Informatik, Freie Universität Berlin, Berlin, Germany

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  3. Diego Alberto Oliva Navarro

    1. Tecnológico de Monterrey, Campus Guadalajara, Zapopan, Mexico

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  • Discusses recent advances and alternative developments in Evolutionary Computation
  • Highlights nonconventional operators which prove to be effective in adapting a determined EC method to a specific problem
  • Consists of self-contained chapters that can be read independently from the others
  • Includes supplementary material: sn.pub/extras

Part of the book series: Studies in Computational Intelligence (SCI, volume 629)

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Table of contents (9 chapters)

  1. Front Matter

    Pages i-xiv
    Download chapter PDF

  2. Introduction

    • Erik Cuevas, Margarita Arimatea Díaz Cortés, Diego Alberto Oliva Navarro
    Pages 1-8

  3. A Swarm Global Optimization Algorithm Inspired in the Behavior of the Social-Spider

    • Erik Cuevas, Margarita Arimatea Díaz Cortés, Diego Alberto Oliva Navarro
    Pages 9-33

  4. A States of Matter Algorithm for Global Optimization

    • Erik Cuevas, Margarita Arimatea Díaz Cortés, Diego Alberto Oliva Navarro
    Pages 35-54

  5. The Collective Animal Behavior method

    • Erik Cuevas, Margarita Arimatea Díaz Cortés, Diego Alberto Oliva Navarro
    Pages 55-81

  6. An Evolutionary Computation Algorithm based on the Allostatic Optimization

    • Erik Cuevas, Margarita Arimatea Díaz Cortés, Diego Alberto Oliva Navarro
    Pages 83-100

  7. Optimization Based on the Behavior of Locust Swarms

    • Erik Cuevas, Margarita Arimatea Díaz Cortés, Diego Alberto Oliva Navarro
    Pages 101-120

  8. Reduction of Function Evaluations by using an evolutionary computation algorithm

    • Erik Cuevas, Margarita Arimatea Díaz Cortés, Diego Alberto Oliva Navarro
    Pages 121-152

  9. Collective Animal Behavior Algorithm for Multimodal Optimization Functions

    • Erik Cuevas, Margarita Arimatea Díaz Cortés, Diego Alberto Oliva Navarro
    Pages 153-174

  10. Social-Spider Algorithm for Constrained Optimization

    • Erik Cuevas, Margarita Arimatea Díaz Cortés, Diego Alberto Oliva Navarro
    Pages 175-202
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Keywords

About this book

The goal of this book is to present advances that discuss alternative Evolutionary Computation (EC) developments and non-conventional operators which have proved to be effective in the solution of several complex problems. The book has been structured so that each chapter can be read independently from the others. The book contains nine chapters with the following themes: 1) Introduction, 2) the Social Spider Optimization (SSO), 3) the States of Matter Search (SMS), 4) the collective animal behavior (CAB) algorithm, 5) the Allostatic Optimization (AO) method, 6) the Locust Search (LS) algorithm, 7) the Adaptive Population with Reduced Evaluations (APRE) method, 8) the multimodal CAB, 9) the constrained SSO method.

Authors and Affiliations

  • Departamento de Electrónica, CUCEI, Universidad de Guadalajara, Guadalajara, Mexico

    Erik Cuevas

  • Institut für Informatik, Freie Universität Berlin, Berlin, Germany

    Margarita Arimatea Díaz Cortés

  • Tecnológico de Monterrey, Campus Guadalajara, Zapopan, Mexico

    Diego Alberto Oliva Navarro

Bibliographic Information

  • Book Title: Advances of Evolutionary Computation: Methods and Operators

  • Authors: Erik Cuevas, Margarita Arimatea Díaz Cortés, Diego Alberto Oliva Navarro

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-319-28503-0

  • Publisher: Springer Cham

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer International Publishing Switzerland 2016

  • Hardcover ISBN: 978-3-319-28502-3Published: 08 February 2016

  • Softcover ISBN: 978-3-319-80366-1Published: 31 March 2018

  • eBook ISBN: 978-3-319-28503-0Published: 20 January 2016

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: XIV, 202

  • Number of Illustrations: 43 b/w illustrations, 5 illustrations in colour

  • Topics: Computational Intelligence, Artificial Intelligence

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