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

• Published in: Advances in Artificial Intelligence and Soft Computing pp. 389 - 400
• Main Author: Zelinka, Ivan
• Format: Book Chapter
• Language: English
• Published: Cham Springer International Publishing 2015
• Series: Lecture Notes in Computer Science
• Subjects: Algorithm; Complex networks; Dynamics; Evolution
• ISBN: 9783319270593; 3319270591
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-319-27060-9_32

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.