Generalized Evolutionary Algorithm based on Tsallis Statistics
  Generalized evolutionary algorithm based on Tsallis canonical distribution is
proposed. The algorithm uses Tsallis generalized canonical distribution to
weigh the configurations for `selection' instead of Gibbs-Boltzmann
distribution. Our simulation results show that for an appropriate choice of
non-extensive index that is offered by Tsallis statistics, evolutionary
algorithms based on this generalization outperform algorithms based on
Gibbs-Boltzmann distribution.
