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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
Clasificación:Libro Electrónico
Autores principales: Cuevas, Erik (Autor), Díaz Cortés, Margarita Arimatea (Autor), Oliva Navarro, Diego Alberto (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2016.
Edición:1st ed. 2016.
Colección:Studies in Computational Intelligence, 629
Temas:
Acceso en línea:Texto Completo

MARC

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505 0 |a 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. . 
520 |a 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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700 1 |a Oliva Navarro, Diego Alberto.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
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