A self-organizing genetic algorithm for finding a global optimum of the goal function with unknown relief is proposed. To find a global extremum, a unique launch of the algorithm is required. The self- organization principles are implemented in constructing the algorithm via the competition of various reproduc- tion and mutation schemes, as well as via the adjustment of the number of parents in multiparent reproduction schemes in the course of operation of the algorithm, which provides an improved efficiency of these schemes. The convergence of the developed algorithm is proved.
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