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Erschienen in:
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2015 | OriginalPaper | Buchkapitel

On Analysis and Performance Improvement of Evolutionary Algorithms Based on its Complex Network Structure

A Summary Overview

verfasst von : Ivan Zelinka

Erschienen in: Advances in Artificial Intelligence and Soft Computing

Verlag: Springer International Publishing

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Abstract

In this participation there is sketched and explained mutual intersection between complex networks and evolutionary computation including summarization of our previous results. It is sketched how dynamics of evolutionary algorithm can be converted into a complex network and based on its properties like degree centrality etc. can be improved performance of used evolutionary algorithm. Results presented here are currently numerical demonstration rather than theoretical mathematical proofs. Paper discusses results from differential evolution, self-organizing migrating algorithm, genetic algorithms and artificial bee colony. We open question whether evolutionary algorithms really create complex network structures and whether this knowledge can be successfully used like feedback for control of evolutionary dynamics and its improvement in order to increase the performance of evolutionary algorithms.

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Vorheriges Kapitel Energy Efficient Routing Based on NSGA-II for Context Parameters Aware Sensor Networks
Nächstes Kapitel Scheduling Projects by a Hybrid Evolutionary Algorithm with Self-Adaptive Processes
Fußnoten
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Metadaten
Titel
On Analysis and Performance Improvement of Evolutionary Algorithms Based on its Complex Network Structure
verfasst von
Ivan Zelinka
Copyright-Jahr
2015
Buch
Advances in Artificial Intelligence and Soft Computing

Print ISBN: 978-3-319-27059-3

Electronic ISBN: 978-3-319-27060-9

Copyright-Jahr: 2015

DOI
https://doi.org/10.1007/978-3-319-27060-9_32

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