Continuous optimization using cellular automata by choosing the evolution rule

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Authors: Bondarenko D. O., Evsyutin O. O., Raschupkina A. V.

Annotation: This article develops previous works made by authors about synthesis of continuous optimization algorithms using modification of cellular automata model: the cellular automata with goal function. The main difference is an adaptive choosing of cellular automata evolution rule by comparing their convergence speed. It was shown, that this method allows better convergence indexes of cellular automata dynamic to goal function optimum, rather than using fixed evolution rule composition.

Keywords: continuous optimization, cellular automata, cellular automata dynamic with goal function, monte- carlo methods