Geodesic
Characterization of solutions of strong-weak convex programming problems
Sbornik. Mathematics, Tome 212 (2021) no. 6, pp. 782-809 Cet article a éte moissonné depuis la source Math-Net.Ru

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Finite-dimensional problems of minimizing a strongly or weakly convex function on a strongly or weakly convex set are considered. Necessary and sufficient conditions for solutions of such problems are presented, which are based on estimates for the behaviour of the objective function on the feasible set taking account of the parameters of strong or weak convexity, as well as certain local features of the set and the function. The mathematical programming problem is considered separately for strongly and weakly convex functions. In addition, necessary conditions for a global and a local solution with differentiable objective function are found, in which a ‘strong’ stationarity condition is assumed to hold. Bibliography: 33 titles.
Keywords: strongly and weakly convex sets and functions, subdifferential, Lagrangian function, radius of local minimum, strong stationarity condition. 
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S. I. Dudov; M. A. Osiptsev. Characterization of solutions of strong-weak convex programming problems. Sbornik. Mathematics, Tome 212 (2021) no. 6, pp. 782-809. http://geodesic.mathdoc.fr/item/SM_2021_212_6_a1/

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