Abstract
Nonconvex optimization problems with an inequality constraint given by the difference of two convex functions (by a d.c. function) are considered. Two methods for finding local solutions to this problem are proposed that combine the solution of partially linearized problems and descent to a level surface of the d.c. function. The convergence of the methods is analyzed, and stopping criterions are proposed. The methods are compared by testing them in a numerical experiment.
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Original Russian Text © T.V. Gruzdeva, A.S. Strekalovsky, 2007, published in Zhurnal Vychislitel’noi Matematiki i Matematicheskoi Fiziki, 2007, Vol. 47, No. 3, pp. 397–413.
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Gruzdeva, T.V., Strekalovsky, A.S. Local search in problems with nonconvex constraints. Comput. Math. and Math. Phys. 47, 381–396 (2007). https://doi.org/10.1134/S0965542507030049
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DOI: https://doi.org/10.1134/S0965542507030049