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.
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Davendra, D., Zelinka, I., Senkerik, R., Pluhacek, M. (2014). Complex Network Analysis of Evolutionary Algorithms Applied to Combinatorial Optimisation Problem. In: Kömer, P., Abraham, A., Snášel, V. (eds) Proceedings of the Fifth International Conference on Innovations in Bio-Inspired Computing and Applications IBICA 2014. Advances in Intelligent Systems and Computing, vol 303. Springer, Cham. https://doi.org/10.1007/978-3-319-08156-4_15
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DOI: https://doi.org/10.1007/978-3-319-08156-4_15
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08155-7
Online ISBN: 978-3-319-08156-4
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