Advances of evolutionary computation methods and operators

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 fr...

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Detalles Bibliográficos
Autores principales: Cuevas, Erik, Díaz Cortés, Margarita Arimatea, Oliva Navarro, Diego Alberto
Lenguaje:eng
Publicado: Springer 2016
Materias:
Engineering
Acceso en línea:https://dx.doi.org/10.1007/978-3-319-28503-0
http://cds.cern.ch/record/2128094
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author Cuevas, Erik
Díaz Cortés, Margarita Arimatea
Oliva Navarro, Diego Alberto
author_facet Cuevas, Erik
Díaz Cortés, Margarita Arimatea
Oliva Navarro, Diego Alberto
author_sort Cuevas, Erik
collection CERN
description 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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institution Organización Europea para la Investigación Nuclear
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publishDate 2016
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spelling cern-21280942021-04-21T19:49:11Zdoi:10.1007/978-3-319-28503-0http://cds.cern.ch/record/2128094engCuevas, ErikDíaz Cortés, Margarita ArimateaOliva Navarro, Diego AlbertoAdvances of evolutionary computation methods and operatorsEngineeringThe 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.Springeroai:cds.cern.ch:21280942016
spellingShingle Engineering
Cuevas, Erik
Díaz Cortés, Margarita Arimatea
Oliva Navarro, Diego Alberto
Advances of evolutionary computation methods and operators
title Advances of evolutionary computation methods and operators
title_full Advances of evolutionary computation methods and operators
title_fullStr Advances of evolutionary computation methods and operators
title_full_unstemmed Advances of evolutionary computation methods and operators
title_short Advances of evolutionary computation methods and operators
title_sort advances of evolutionary computation methods and operators
topic Engineering
url https://dx.doi.org/10.1007/978-3-319-28503-0
http://cds.cern.ch/record/2128094
work_keys_str_mv AT cuevaserik advancesofevolutionarycomputationmethodsandoperators
AT diazcortesmargaritaarimatea advancesofevolutionarycomputationmethodsandoperators
AT olivanavarrodiegoalberto advancesofevolutionarycomputationmethodsandoperators

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