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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
Autores principales: Cuevas, Erik, Díaz Cortés, Margarita Arimatea, Oliva Navarro, Diego Alberto
Lenguaje:eng
Publicado: Springer 2016
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-3-319-28503-0
http://cds.cern.ch/record/2128094
Descripción
Sumario: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.