Advances of Evolutionary Computation: Methods and Operators

Nonfiction, Computers, Advanced Computing, Artificial Intelligence, General Computing
Cover of the book Advances of Evolutionary Computation: Methods and Operators by Erik Cuevas, Margarita Arimatea Díaz Cortés, Diego Alberto Oliva Navarro, Springer International Publishing
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Author: Erik Cuevas, Margarita Arimatea Díaz Cortés, Diego Alberto Oliva Navarro ISBN: 9783319285030
Publisher: Springer International Publishing Publication: January 20, 2016
Imprint: Springer Language: English
Author: Erik Cuevas, Margarita Arimatea Díaz Cortés, Diego Alberto Oliva Navarro
ISBN: 9783319285030
Publisher: Springer International Publishing
Publication: January 20, 2016
Imprint: Springer
Language: English

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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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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