Advances of evolutionary computation : methods and operators

Responsibility: Erik Cuevas, Margarita Arimatea Díaz Cortés, Diego Alberto Oliva Navarro.
Language: English. English.
Digital: text file; PDF
Publication: Cham : Springer, 2016.
Physical description: 1 online resource (xiv, 202 pages) : illustrations (some color)
Series: Studies in computational intelligence ; v. 629. 1860-949X

Online

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Description

Creators/Contributors

Contributor: Cuevas, Erik author.; Díaz Cortés, Margarita Arimatea, author.; Oliva Navarro, Diego Alberto, author.

Contents/Summary

Bibliography

Includes bibliographical references.

Contents

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.

Summary

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.

Subjects

Subjects: Evolutionary computation.; Artificial intelligence.; Computers > Intelligence (AI) & Semantics.

Bibliographic information

Publication date: 2016
Series: Studies in Computational Intelligence, 1860-949X ; volume 629
ISBN: 9783319285030 (electronic bk.); 3319285033 (electronic bk.); 3319285025 (print); 9783319285023 (print); 9783319285023
DOI: 10.1007/978-3-319-28503-0