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Advances of Evolutionary Computation

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Advances of Evolutionary Computation Synopsis

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 e?ective 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.

About This Edition

ISBN: 9783319285023
Publication date:
Author: Erik Cuevas, Margarita Arimatea Díaz Cortés, Diego Oliva
Publisher: Springer an imprint of Springer International Publishing
Format: Hardback
Pagination: 202 pages
Series: Studies in Computational Intelligence
Genres: Artificial intelligence