Fine-grained Parallel Genetic Algorithm: a Stochastic Optimisation Method

نویسندگان

  • A. Muhammad
  • A. Bargiela
  • G. King
چکیده

This paper presents a fine-grained parallel genetic algorithm with mutation rate as a control parameter. The function of the mutation rate is similar to the function of temperature parameter in the simulated annealing [Lundy’86, Otten’89, and Romeo’85]. The parallel genetic algorithm presented here is based on a Markov chain [Kemeny’60] model. It has been proved that fine-grained parallel genetic algorithm is an ergodic Markov chain and it converges to the stationary distribution.

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تاریخ انتشار 2002