Genetic algorithms (GA) belong to so called biologically based methods. There are many applications of genetic algorithms in different fields. Some GA are used in business and biology, some of them in technical applications. A characteristic feature of GA is seeking "better" populations of genetics chains by means of random choice rules applied appropriately to the operations of reproduction, crossing and mutation. In this paper we are considering two tiny examples: GA for solving the travelers problem and the GA for providing market operations. Results seem to be encouraging.
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