Advances of Evolutionary Computation: Methods and Operators

✍ Scribed by Erik Cuevas, Margarita Arimatea Díaz Cortés, Diego Alberto Oliva Navarro (auth.)

Publisher: Springer International Publishing
Year: 2016
Tongue: English
Leaves: 214
Series: Studies in Computational Intelligence 629
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ 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 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.

✦ Table of Contents

Front Matter....Pages i-xiv
Introduction....Pages 1-8
A Swarm Global Optimization Algorithm Inspired in the Behavior of the Social-Spider....Pages 9-33
A States of Matter Algorithm for Global Optimization....Pages 35-54
The Collective Animal Behavior method....Pages 55-81
An Evolutionary Computation Algorithm based on the Allostatic Optimization....Pages 83-100
Optimization Based on the Behavior of Locust Swarms....Pages 101-120
Reduction of Function Evaluations by using an evolutionary computation algorithm....Pages 121-152
Collective Animal Behavior Algorithm for Multimodal Optimization Functions....Pages 153-174
Social-Spider Algorithm for Constrained Optimization....Pages 175-202

✦ Subjects

Computational Intelligence; Artificial Intelligence (incl. Robotics)

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