Abstract
A numerical algorithm for minimizing a convex function on a smooth surface is proposed. The algorithm is based on reducing the original problem to a sequence of convex programming problems. Necessary extremum conditions are examined, and the convergence of the algorithm is analyzed.
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Original Russian Text © Yu.A. Chernyaev, 2016, published in Zhurnal Vychislitel’noi Matematiki i Matematicheskoi Fiziki, 2016, Vol. 56, No. 3, pp. 387–393.
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Chernyaev, Y.A. Numerical algorithm for solving mathematical programming problems with a smooth surface as a constraint. Comput. Math. and Math. Phys. 56, 376–381 (2016). https://doi.org/10.1134/S0965542516030027
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DOI: https://doi.org/10.1134/S0965542516030027