Analysing evolutionary algorithm dynamics using complex network theory: a primary study. (1st January 2013) - Pan, Weifeng; Wang, Jing; Yuan, Chengxiang; Zhang, Jianming; Xue, Hongyan
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.