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Performance Improvement of Simple Bacteria Cooperative Optimization through Rank-based Perturbation

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2011, 16(12), pp.23-32
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science

Sung Hoon Jung 1

1한성대학교

Accredited

ABSTRACT

The simple bacteria cooperative optimization (sBCO) algorithm that we developed as one of optimization algorithms has shown relatively good performances, but their performances were limited by step-by-step movement of individuals at a time. In order to solve this problem, we proposed a new method that assigned a speed to each individual according to its rank and it was confirmed that it improved the performances of sBCO in some degree. In addition to the assigning of speed to the individuals, we employed a new mutation operation that most existing evolutionary algorithms used in order to enhance the performances of sBCO in this paper. A specific percent of bad individuals are mutated within an area that is proportion to the rank of the individual in the mutation operation. That is, Gaussian noise of large standard deviation is added as the fitness of individuals is low. From this, the probability that the individuals with lower ranks can be located far from its parent will be increased. This causes that the probability of falling into local optimum areas is decreased and the probability of fast escaping the local optimum areas is increased. From experimental results with four function optimization problems, we showed that the performances of sBCO with mutation operation and individual speed were increased. If the optimization function is quite complex, however, the performances are not always better. We should devise a new method for solving this problem as a further work.

Citation status

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