The paper discusses two evolutionary strategies (μ+)λ and (μ,)λ used for solving complicated problem s of numerical optimization. The strategies discussed in the paper, inspired by biological evolution and genetics, operate in populations of the sizes μand λof potential solutions with a deterministic selection procedure. The correctness of the operation of the strategy as a search for a global minimum of a criterion function is exemplified by the minimization of an Ackley function and the estimation of parameters of a regression function of the second kind.

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