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Evolution based on chromosome affinity from a network perspective

Author

Listed:
  • Monteiro, R.L.S.
  • Fontoura, J.R.A.
  • Carneiro, T.K.G.
  • Moret, M.A.
  • Pereira, H.B.B.

Abstract

Recent studies have focused on models to simulate the complex phenomenon of evolution of species. Several studies have been performed with theoretical models based on Darwin’s theories to associate them with the actual evolution of species. However, none of the existing models include the affinity between individuals using network properties. In this paper, we present a new model based on the concept of affinity. The model is used to simulate the evolution of species in an ecosystem composed of individuals and their relationships. We propose an evolutive algorithm that incorporates the degree centrality and efficiency network properties to perform the crossover process and to obtain the network topology objective, respectively. Using a real network as a starting point, we simulate its evolution and compare its results with the results of 5788 computer-generated networks.

Suggested Citation

  • Monteiro, R.L.S. & Fontoura, J.R.A. & Carneiro, T.K.G. & Moret, M.A. & Pereira, H.B.B., 2014. "Evolution based on chromosome affinity from a network perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 403(C), pages 276-283.
    • Handle: RePEc:eee:phsmap:v:403:y:2014:i:c:p:276-283
    DOI: 10.1016/j.physa.2014.02.019
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    References listed on IDEAS

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    Cited by:

    1. Wu, Zhenyu & Zou, Ming, 2014. "Modeling social tagging using latent interaction potential," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 125-133.

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