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Information × Registration Number 0222U000966, 0119U101608 , R & D reports Title New methods for wellposedness investigation and solving of discrete optimization problems, variational inequalities and their applications popup.stage_title Head Serhiienko Ivan V., Доктор фізико-математичних наук Registration Date 22-01-2022 Organization Department for special training National academy of science of Ukraine at Kiev University popup.description2  The conditions of existence and optimality of solutions of vector lexicographic optimization problems are established. For a vector optimization problem with continuous criterion functions and a set of feasible solutions of an arbitrary structure, the conditions of stability with respect to perturbations of the input data of the vector criterion are determined. A two-stage Bregman method of extrapolation from the past with an adaptive rule of step size selection is proposed. A new operator extrapolation algorithm with Bregman projection and generalized Alber projection is proposed to solve variational inequalities in Hilbert and uniformly convex Banach spaces. A new algorithm is proposed to solve two-level monotone variational inequalities. The weak convergence of the two-stage proximal algorithm for equilibrium problems in Hilbert space is proved. Under the condition of sharp equilibrium, finite convergence is proved. New adaptive two-stage proximal algorithms for equilibrium problems in Hadamard metric spaces are proposed. Product Description popup.authors Lebedeva Tetiana T. Lyashko Sergiy I. Semenova Nataliia V. Sergienko Ivan V. popup.nrat_date 2022-03-09 Close