Complex Network Analysis of Discrete Self-organising Migrating Algorithm

  • Donald Davendra
  • Ivan Zelinka
  • Roman Senkerik
  • Michal Pluhacek
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 289)


This research analyses the development of a complex network in the swarm based Discrete Self-Organising Migrating Algorithm (DSOMA). The main aim is to evaluate if a complex network is generated in DSOMA, and how the population can be evaluated when the objective is to optimise the flow shop scheduling with blocking problem. The population is evaluated as a complex network over a number of migrations, and different attributes such as adjacency graph, minimal cut, degree centrality, closeness centrality, betweenness centrality, Katz centrality, mean neighbour degree, k-Clique, k-Plan, k-Club, k-Clan and community graph plots are analysed. From the results, it can be concluded that an DSOMA population does behave like a complex network, and therefore can be analysed as such, in order to obtain information about population development.


Evolutionary algorithm complex network flow shop scheduling with blocking 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Donald Davendra
    • 1
  • Ivan Zelinka
    • 1
  • Roman Senkerik
    • 2
  • Michal Pluhacek
    • 2
  1. 1.Faculty of Electrical Engineering and Computer ScienceVŠB - Technical University of OstravaOstrava-PorubaCzech Republic
  2. 2.Faculty of Applied InformaticsTomas Bata University in ZlinZlinCzech Republic

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