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Advances of evolutionary computation...
~
Cuevas, Erik.
Advances of evolutionary computationmethods and operators /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Advances of evolutionary computationby Erik Cuevas, Margarita Arimatea Diaz Cortes, Diego Alberto Oliva Navarro.
Reminder of title:
methods and operators /
Author:
Cuevas, Erik.
other author:
Diaz Cortes, Margarita Arimatea.
Published:
Cham :Springer International Publishing :2016.
Description:
xiv, 202 p. :ill., digital ;24 cm.
Contained By:
Springer eBooks
Subject:
Evolutionary computation.
Online resource:
http://dx.doi.org/10.1007/978-3-319-28503-0
ISBN:
9783319285030$q(electronic bk.)
Advances of evolutionary computationmethods and operators /
Cuevas, Erik.
Advances of evolutionary computation
methods and operators /[electronic resource] :by Erik Cuevas, Margarita Arimatea Diaz Cortes, Diego Alberto Oliva Navarro. - Cham :Springer International Publishing :2016. - xiv, 202 p. :ill., digital ;24 cm. - Studies in computational intelligence,v.6291860-949X ;. - Studies in computational intelligence ;v. 216..
Introduction -- A Swarm Global Optimization Algorithm Inspired in the Behavior of the Social-spider -- A States of Matter Algorithm for Global Optimization -- An Algorithm for Global Optimization Inspired by Collective Animal Behavior -- A Bio-inspired Evolutionary Algorithm: Allostatic Optimization -- Optimization Based on the Behavior of Locust Swarms.
The goal of this book is to present advances that discuss alternative Evolutionary Computation (EC) developments and non-conventional operators which have proved to be effective in the solution of several complex problems. The book has been structured so that each chapter can be read independently from the others. The book contains nine chapters with the following themes: 1) Introduction, 2) the Social Spider Optimization (SSO), 3) the States of Matter Search (SMS), 4) the collective animal behavior (CAB) algorithm, 5) the Allostatic Optimization (AO) method, 6) the Locust Search (LS) algorithm, 7) the Adaptive Population with Reduced Evaluations (APRE) method, 8) the multimodal CAB, 9) the constrained SSO method.
ISBN: 9783319285030$q(electronic bk.)
Standard No.: 10.1007/978-3-319-28503-0doiSubjects--Topical Terms:
231709
Evolutionary computation.
LC Class. No.: QA76.618
Dewey Class. No.: 006.3823
Advances of evolutionary computationmethods and operators /
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methods and operators /
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by Erik Cuevas, Margarita Arimatea Diaz Cortes, Diego Alberto Oliva Navarro.
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Introduction -- A Swarm Global Optimization Algorithm Inspired in the Behavior of the Social-spider -- A States of Matter Algorithm for Global Optimization -- An Algorithm for Global Optimization Inspired by Collective Animal Behavior -- A Bio-inspired Evolutionary Algorithm: Allostatic Optimization -- Optimization Based on the Behavior of Locust Swarms.
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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.
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Engineering (Springer-11647)
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EB QA76.618 C965 2016
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http://dx.doi.org/10.1007/978-3-319-28503-0
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