Complex Network Analysis of Evolutionary Algorithms Applied to Combinatorial Optimisation Problem

19Citations
Citations of this article
4Readers
Mendeley users who have this article in their library.
Get full text

Abstract

This research analyses the development of a complex network in an evolutionary algorithm (EA). The main aim is to evaluate if a complex network is generated in an EA, and how the population can be evaluated when the objective is to optimise an NP-hard combinatorial optimisation problem. The population is evaluated as a complex network over a number of generations, and different attributes such as adjacency graph, minimal cut, degree centrality, closeness centrality, betweenness centrality, k-Clique, k-Club, k-Clan and community graph plots are analysed. From the results, it can be concluded that an EA population does behave like a complex network, and therefore can be analysed as such, in order to obtain information about population development. © Springer International Publishing Switzerland 2014.

Cite

CITATION STYLE

APA

Davendra, D., Zelinka, I., Senkerik, R., & Pluhacek, M. (2014). Complex Network Analysis of Evolutionary Algorithms Applied to Combinatorial Optimisation Problem. In Advances in Intelligent Systems and Computing (Vol. 303, pp. 141–150). Springer Verlag. https://doi.org/10.1007/978-3-319-08156-4_15

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free