Solving a class of nonconvex quadratic programs by inertial DC algorithms

Người báo cáo: Nguyễn Năng Thiều

Thời gian: 9h00 đến 11h00 sáng thứ Tư ngày 05.11.2025.

Địa điểm: Phòng 508 nhà A6 Viện Toán học

Tóm tắt: In this talk, we present two inertial DC algorithms for indefinite quadratic programs under linear constraints (IQPs), where the constraint set may be unbounded. Using a qualification condition involving the normal cones of unbounded pseudo-faces of the polyhedral convex constraint set, the recession cones of the corresponding faces, and the quadratic form defining the objective function, we show that the resulting iteration sequences are bounded whenever the given IQP has a finite optimal value. Any cluster point of such a sequence is a Karush-Kuhn-Tucker point. Moreover, all cluster points of a given iteration sequence belong to a single connected component of the Karush-Kuhn-Tucker point set.

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Xuất bản mới
Le Thi Hong Hanh, Dương Trọng Luyện, Nguyễn Minh Trí, Nontrivial Solutions to Boundary Value Problems for Semilinear $\Delta ^{\alpha ,\beta }_{\alpha _1,\beta _1}$-Differential Equations, Analysis and PDE in Developing Countries, Trends in Mathematics (TM, volume 17) (2026) pp 27–35, Birkhäuser/Springer, Cham, 2026 ISBN: 978-3-032-14210-8; 978-3-032-14211-5
Adam Czornik, Đoàn Thái Sơn, Nguyễn Thị Thu Sương, Pole Placement Theorem for Linear Measurable Time-Varying Control Systems with Single Input, SIAM Journal on Control and Optimization, Vol. 64, Iss. 4 (2026)
Đinh Nho Hào, Maxim Shishlenin, Van Ba Cong, Stable Numerical Solution to Multi-dimensional Nonlinear Inverse Heat Conduction Problems via Artificial Neural Networks, Lobachevskii Journal of Mathematics, Volume 47, pages 1213–1232 (2026)