Analysing evolutionary algorithm dynamics using complex network theory: a primary study Online publication date: Sat, 10-May-2014
by Weifeng Pan; Jing Wang; Chengxiang Yuan; Jianming Zhang; Hongyan Xue
International Journal of Computing Science and Mathematics (IJCSM), Vol. 4, No. 4, 2013
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.
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