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Advances of Evolutionary Computation: Methods and Operators

Advances of Evolutionary Computation: Methods and Operators
Springer | Computational Intelligence and Complexity | January 7, 2016 | ISBN-10: 3319285025 | 202 pages | pdf | 15.78 mb
Authors: Cuevas, Erik, Díaz Cortés, Margarita Arimatea, Oliva Navarro, Diego Alberto
Discusses recent advances and alternative developments in Evolutionary Computation
Highlights nonconventional operators which prove to be effective in adapting a determined EC method to a specific problem
Consists of self-contained chapters that can be read independently from the others


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.

Number of Illustrations and Tables
5 illus., 43 in colour
Topics
Computational Intelligence
Artificial Intelligence (incl. Robotics)

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