Performance of Exponential Evolutionary Programming

H. Narihisa, K. Kohmoto, T. Kumon, and K. Katayama (Japan)


Evolutionary programming, Evolutionary computation, Evolutionary engineering, Exponential mutation


In this paper, an exponential evolutionary programming (EEP) that uses a mutation operator based on double expo nential probability distribution is investigated. Hitherto, the mutation operator of evolutionary programming is mainly based on normal probability distribution or Cauchy proba bility distribution to evolve solutions for given optimization problems. The double exponential probability distribution with one positive real valued parameter has some positive amount second moment and is symmetric with respect to origin. The variance of this probability distribution is nei ther infinite as Cauchy distribution, nor unit as standardized normal distribution. Therefore, the amount of this variance is controllable by the value of this parameter. The results of computational experiment show the effectiveness of EEP when applied to the optimization problems.

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