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A New Evolutionary Algorithm Based on Cellular Automata

Tapas Kumar, I. M. S. Lamba, G. Sahoo


The field of evolutionary computation is itself an evolving community of people, ideas, and applications. To derive a solution of a problem from a population of individuals, over a number of generations, evolutionary computing techniques has been used as an explicit function. In this paper a new evolutionary algorithm, called the CA-EA (Cellular Automata Based Evolutionary Algorithm), is proposed. This algorithm is a combination of evolutionary algorithms and the Cellular Automata (CA). Our motivation here is to discuss how cellular automata techniques can be involved on evolutionary algorithm. A study of cellular automata based evolutionary computation in genetic analysis is an inherent problem. But the key problems of genetic analysis are very sensitive in the detection of fitness cells. Here, we consider an interactive step so as to get a maximum amount of information that can be shared for the best evaluation of individual fitness cell.


Fitness Analysis, Genetic Algorithm, CA-EA Model, Cellular Automata.

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