Title: Analysing evolutionary algorithm dynamics using complex network theory: a primary study

Authors: Weifeng Pan; Jing Wang; Chengxiang Yuan; Jianming Zhang; Hongyan Xue

Addresses: School of Computer Science and Information Engineering, Zhejiang Gongshang University, Hangzhou 310018, China ' School of Software and Communication Engineering, Jiangxi University of Finance and Economics, Nanchang 330013, China ' School of Computer Science and Information Engineering, Zhejiang Gongshang University, Hangzhou 310018, China ' School of Computer Science and Information Engineering, Zhejiang Gongshang University, Hangzhou 310018, China ' School of Computer Science and Information Engineering, Zhejiang Gongshang University, Hangzhou 310018, China

Abstract: Evolutionary algorithms (EAs) are capable to effectively solve hard problems from various fields. When applying EAs to solve specific problems, a huge amount of data will be produced in the process. Due to lack of suitable tools, people seldom explore the rich information in algorithm exclusions, making we are in dark of the dynamics of EAs. Inspired by complex networks research, in this paper, we present a new method to analyse the dynamics of EAs in the form of complex networks. It uses a network model to describe the individuals and their gene relationships. It introduces the parameters of the complex network theory to characterise the evolution of the network. Some properties hidden in the dynamics of EAs are uncovered.

Keywords: evolutionary algorithms; complex network theory; crossover; mutation; evolutionary algorithm dynamics; network modelling; gene relationships; hidden properties.

DOI: 10.1504/IJCSM.2013.058059

International Journal of Computing Science and Mathematics, 2013 Vol.4 No.4, pp.339 - 353

Received: 04 May 2013
Accepted: 01 Jul 2013

Published online: 01 Dec 2013 *

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